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<h1 itemprop="headline" class="js-feed-post-title t-feed__post-popup__title t-title t-title_xxs">Что будет, если изменить количество виртуальных нод в Apache Cassandra? Часть 2</h1>
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<div itemprop="articleBody" class="js-feed-post-text t-feed__post-popup__text t-text t-text_md"><section>Продолжаем разбираться, как новое значение в Apache Cassandra 4.0 сказывается на кластере и его поведении. Первая часть материала — <a href="https://slurm.io/tpost/dij1g630t1-chto-budet-esli-izmenit-kolichestvo-virt" target="_blank" rel="noreferrer noopener">по ссылке.</a> <br /> <br /><h2 class="t-redactor__h2"><strong>Добавляем стойки</strong></h2>Опытный пользователь Cassandra заметит, что мы тестили распределение токенов в кластерах только в одной стойке. Давайте добавим стойки, чтобы повысить доступность при использовании виртуальных нод. Если стоек несколько, Cassandra попытается распределить реплики по ним, чтобы в одной стойке не было двух одинаковых диапазонов.<br /><br /><strong>Надо настроить кластер таким образом, чтобы в одном датацентре число стоек совпадало с коэффициентом репликации.</strong><br /><br />Возьмем предыдущий пример, где для параметра num_tokens мы выбрали значение <strong>3</strong>, только на этот раз определим в тестовом кластере три стойки. Настраиваем и запускаем ноды в ccm. Тестовый кластер выглядит так: <a href="https://xpaste.pro/p/Y3uou9TP" target="_blank" rel="nofollow noreferrer noopener"><em>https://xpaste.pro/p/Y3uou9TP</em></a><br /><br />Кластер все равно не сбалансирован. Это не так важно. Главное, мы видим, что теперь у нас три стойки и на каждой по две ноды. Снова создаем тестовое keyspace и заполняем его с помощью cqlsh. Смотрим, как распределено кольцо токенов (опять добавляем буквенное обозначение).<br /><br /><figure data-alt="" data-src="https://static.tildacdn.com/tild6435-3534-4566-a261-386364616632/1.png" data-new-tab="false" contenteditable="false"><img src="https://static.tildacdn.com/tild6435-3534-4566-a261-386364616632/1.png" alt="" /></figure><a href="https://xpaste.pro/p/b3KCa0SC" target="_blank" rel="nofollow noreferrer noopener"><em>Скопировать код</em></a><br /><br />Снова берем выходные данные ccm node1 nodetool describering test_keyspace и меняем номера токенов на буквы.<br /><br /><em>Посмотреть, как это выглядит: </em><a href="https://xpaste.pro/p/fXWNJQUO"><em>https://xpaste.pro/p/fXWNJQUO</em></a><br /><br />Наконец, смотрим, как диапазоны токенов распределены по нодам:<br /><br /><figure data-alt="" data-src="https://static.tildacdn.com/tild3436-6132-4264-a535-396335613561/q2-p-fiavnz_mz1fkhgg.png" data-new-tab="false" contenteditable="false"><img src="https://static.tildacdn.com/tild3436-6132-4264-a535-396335613561/q2-p-fiavnz_mz1fkhgg.png" alt="" /></figure><br />Судя по назначению токенов, теперь у нас есть полная реплика данных, распределенная по двум узлам в каждой из трех стоек. Если ноды 3 и 6 упадут, мы все равно сможем обслуживать запросы с уровнем согласованности LOCAL_QUORUM. Здесь бросается в глаза нода 3, у которой гораздо больше токенов, чем у других. Ее сосед по стойке, нода 6, наоборот, содержит меньше всего токенов.<br /><br /><h2 class="t-redactor__h2"><strong>Не переборщите с виртуальными нодами</strong></h2>Если при небольшом числе виртуальных нод возникают проблемы распределения, логично предположить, что лучше выбирать число побольше. Но кроме риска потерять доступ к данным при сбое нескольких нод, мы получаем снижение производительности при передаче данных. Чтобы восстановить данные на ноде, Cassandra запускает по одному сеансу восстановления на виртуальную ноду. Сеансы обрабатываются последовательно. Чем больше виртуальных нод, тем больше времени и ресурсов на это уйдет.<br /><br />Чтобы ускорить восстановление при большом количестве виртуальных нод, в версии 3.0 представлено изменение <a href="https://issues.apache.org/jira/browse/CASSANDRA-5220" target="_blank" rel="nofollow noreferrer noopener">CASSANDRA-5220</a>. Благодаря этому Cassandra объединяет несколько диапазонов для набора нод в один сеанс восстановления. Сеанс выполняется дольше, зато их стало меньше.<br /><br />Давайте проверим влияние виртуальных нод на восстановление, проведя простой тест на кластере на реальном оборудовании. Для этого создадим кластер с единичным назначением токенов и запустим восстановление. Затем создадим такой же кластер, но с 256 виртуальными нодами, и снова запустим восстановление. Используем tlp-cluster, чтобы создать кластер Cassandra в AWS со следующими свойствами.<br /><br /><ul><li>Размер инстанса: i3.2xlarge</li><li>Число нод: 12</li><li>Число стоек: 3 (по 4 ноды на стойку)</li><li>Версия Cassandra: 3.11.9</li></ul><br />Команды для сборки кластера: <a href="https://xpaste.pro/p/tAQDU6Mk" target="_blank" rel="nofollow noreferrer noopener"><em>https://xpaste.pro/p/tAQDU6Mk</em></a><br /><br />Выделив оборудование, задаем свойство initial_token для каждой ноды по отдельности. Вычисляем начальные токены для каждой ноды простой командой Python. <br /><br /><em>Посмотреть, как это выглядит: </em><a href="https://xpaste.pro/p/KVietoOz" target="_blank" rel="nofollow noreferrer noopener"><em>https://xpaste.pro/p/KVietoOz</em></a><br /><br />После запуска Cassandra на всех нодах можно загрузить около 3 ГБ данных на ноду с помощью команды tlp-stress. В этой команде мы задаем для keyspace коэффициент репликации 3, а для gc_grace_seconds устанавливаем <em>0</em>. Срок действия хинтов будет истекать сразу после создания, то есть они никогда не попадут на целевую ноду.<br /><br /><em>Посмотреть, как это выглядит: </em><a href="https://xpaste.pro/p/FM0AEI1V" target="_blank" rel="nofollow noreferrer noopener"><em>https://xpaste.pro/p/FM0AEI1V</em></a><br /><br />После загрузки данных статус кластера выглядит так:<br /><br /><figure data-alt="" data-src="https://static.tildacdn.com/tild6138-6466-4438-b830-316132393330/2.png" data-new-tab="false" contenteditable="false"><img src="https://static.tildacdn.com/tild6138-6466-4438-b830-316132393330/2.png" alt="" /></figure><a href="https://xpaste.pro/p/tG06cZXV" target="_blank" rel="nofollow noreferrer noopener"><em>Скопировать код</em></a><br /><br />Запускаем полное восстановление на каждой ноде:<br /><br /><blockquote class="t-redactor__quote"><em>$ source env.sh</em></blockquote><blockquote class="t-redactor__quote"><em>$ c_all "nodetool repair -full tlp_stress"</em></blockquote><br />Время восстановления для каждой ноды:<br /><br /><blockquote class="t-redactor__quote"><em>[2021-01-22 20:20:13,952] Repair command #1 finished in 3 minutes 55 seconds</em></blockquote><blockquote class="t-redactor__quote"><em>[2021-01-22 20:23:57,053] Repair command #1 finished in 3 minutes 36 seconds</em></blockquote><blockquote class="t-redactor__quote"><em>[2021-01-22 20:27:42,123] Repair command #1 finished in 3 minutes 32 seconds</em></blockquote><blockquote class="t-redactor__quote"><em>[2021-01-22 20:30:57,654] Repair command #1 finished in 3 minutes 21 seconds</em></blockquote><blockquote class="t-redactor__quote"><em>[2021-01-22 20:34:27,740] Repair command #1 finished in 3 minutes 17 seconds</em></blockquote><blockquote class="t-redactor__quote"><em>[2021-01-22 20:37:40,449] Repair command #1 finished in 3 minutes 23 seconds</em></blockquote><blockquote class="t-redactor__quote"><em>[2021-01-22 20:41:32,391] Repair command #1 finished in 3 minutes 36 seconds</em></blockquote><blockquote class="t-redactor__quote"><em>[2021-01-22 20:44:52,917] Repair command #1 finished in 3 minutes 25 seconds</em></blockquote><blockquote class="t-redactor__quote"><em>[2021-01-22 20:47:57,729] Repair command #1 finished in 2 minutes 58 seconds</em></blockquote><blockquote class="t-redactor__quote"><em>[2021-01-22 20:49:58,868] Repair command #1 finished in 1 minute 58 seconds</em></blockquote><blockquote class="t-redactor__quote"><em>[2021-01-22 20:51:58,724] Repair command #1 finished in 1 minute 53 seconds</em></blockquote><blockquote class="t-redactor__quote"><em>[2021-01-22 20:54:01,100] Repair command #1 finished in 1 minute 50 seconds</em></blockquote><br />Понадобилось 36 минут 44 секунды.<br /><br />На этом же кластере можно измерить время восстановления, когда используется 256 нод. Делаем следующее.<br /><br /><ul><li>Завершаем работу Cassandra на всех нодах.</li><li>Удаляем содержимое каждого каталога data, commitlog, hints и saved_caches (они находятся в /var/lib/cassandra/ на каждой ноде).</li><li>Задаем для параметра num_tokens в файле конфигурации cassandra.yaml значение 256 и удаляем параметр initial_token.</li><li>Запускаем Cassandra на всех нодах.</li></ul><br />После заполнения кластера данными статус выглядит так:<br /><br /><figure data-alt="" data-src="https://static.tildacdn.com/tild3465-3036-4639-a563-363963663733/3.png" data-new-tab="false" contenteditable="false"><img src="https://static.tildacdn.com/tild3465-3036-4639-a563-363963663733/3.png" alt="" /></figure><a href="https://xpaste.pro/p/X7Dz9fKI" target="_blank" rel="nofollow noreferrer noopener"><em>Скопировать код</em></a><br /><br />Запускаем тот же тест восстановления, что и раньше:<br /><br /><blockquote class="t-redactor__quote"><em>[2021-01-22 22:45:56,689] Repair command #1 finished in 4 minutes 40 seconds</em></blockquote><blockquote class="t-redactor__quote"><em>[2021-01-22 22:50:09,170] Repair command #1 finished in 4 minutes 6 seconds</em></blockquote><blockquote class="t-redactor__quote"><em>[2021-01-22 22:54:04,820] Repair command #1 finished in 3 minutes 43 seconds</em></blockquote><blockquote class="t-redactor__quote"><em>[2021-01-22 22:57:26,193] Repair command #1 finished in 3 minutes 27 seconds</em></blockquote><blockquote class="t-redactor__quote"><em>[2021-01-22 23:01:23,554] Repair command #1 finished in 3 minutes 44 seconds</em></blockquote><blockquote class="t-redactor__quote"><em>[2021-01-22 23:04:40,523] Repair command #1 finished in 3 minutes 27 seconds</em></blockquote><blockquote class="t-redactor__quote"><em>[2021-01-22 23:08:20,231] Repair command #1 finished in 3 minutes 23 seconds</em></blockquote><blockquote class="t-redactor__quote"><em>[2021-01-22 23:11:01,230] Repair command #1 finished in 2 minutes 45 seconds</em></blockquote><blockquote class="t-redactor__quote"><em>[2021-01-22 23:13:48,682] Repair command #1 finished in 2 minutes 40 seconds</em></blockquote><blockquote class="t-redactor__quote"><em>[2021-01-22 23:16:23,630] Repair command #1 finished in 2 minutes 32 seconds</em></blockquote><blockquote class="t-redactor__quote"><em>[2021-01-22 23:18:56,786] Repair command #1 finished in 2 minutes 26 seconds</em></blockquote><blockquote class="t-redactor__quote"><em>[2021-01-22 23:21:38,961] Repair command #1 finished in 2 minutes 30 seconds</em></blockquote><br />Итого — 39 минут 23 секунды.<br /><br />Для 3 ГБ данных на ноду разница терпимая (где-то по 45 секунд на ноду), но мы понимаем, что отставание будет существенным, если на каждой ноде будут сотни гигабайт.<br /><br />К сожалению, такие операции, как инициализация и ребилд датацентра, тоже пострадают от большого числа виртуальных нод. Когда нода передает данные на другую ноду, сеанс передачи открывается для каждого диапазона токенов на ноде. Это приводит к слишком большим издержкам, поскольку данные передаются через JVM.<br /><br /><h2 class="t-redactor__h2"><strong>Проблемы со вторичными индексами</strong></h2>Мало того, большое число виртуальных нод влияет на вторичные индексы. Это связано с тем, как устроен путь чтения.<br /><br />Когда нода-координатор получает от клиента запрос со вторичным индексом, она рассылает его по всем нодам в кластере или датацентре, в зависимости от уровня согласованности. Каждая нода проверяет SSTables для каждого диапазона токенов, назначенного ей, в поисках соответствия этому запросу. Соответствия возвращаются на ноду-координатор.<br /><br />Поэтому чем больше виртуальных нод, тем медленнее отклик для такого запроса. Более того, ухудшение производительности для вторичных индексов резко возрастает при увеличении числа реплик на кластере. Если в нескольких датацентрах есть ноды, использующие много виртуальных нод, вторичные индексы становятся еще менее эффективными.<br /><br /><h2 class="t-redactor__h2"><strong>Новая надежда</strong></h2>Итак, в Cassandra есть свойство, которое существенно упрощает изменение размера кластера. К сожалению, за это приходится платить несбалансированными диапазонами токенов и снижением производительности операций. Но это еще не вся история.<br /><br />Все уже прекрасно знают, что в Apache Cassandra большое число виртуальных нод имеет побочные эффекты. Чтобы решить эту проблему, изобретательные участники сообщества добавили в версию 3.0 <a href="https://issues.apache.org/jira/browse/CASSANDRA-7032" target="_blank" rel="nofollow noreferrer noopener">CASSANDRA-7032</a> — алгоритм распределения токенов, учитывающий реплики, чтобы можно было использовать небольшое значение для num_tokens при сохранении относительно равномерного распределения диапазонов. Сюда входит добавление параметра allocate_tokens_for_keyspace в файл <em>cassandra.yaml</em>. Новый алгоритм используется вместо случайного распределителя токенов. Он назначает существующему пользовательскому keyspace параметр allocate_tokens_for_keyspace.<br /><br />Cassandra, на основе коэффициента репликации для keyspace, рассчитывает значения токенов для ноды при ее добавлении в кластер. В отличие от случайного генератора токенов, генератор, учитывающий реплики, похож на опытного музыканта симфонического оркестра, играющего в унисон с коллегами. До такой степени, что при генерации диапазонов токенов он:<br /><br /><ul><li>Создает начальное состояние кольца токенов.</li><li>Вычисляет кандидатов для новых токенов, разделяя все существующие диапазоны посредине.</li><li>Оценивает ожидаемые улучшения от всех кандидатов, формируя приоритетную очередь.</li><li>Проверяет всех кандидатов в очереди и выбирает лучшую комбинацию.</li><li>Во время выбора токенов пересматривает улучшения кандидатов в очереди.</li></ul><br />Для Cassandra это был большой прогресс, но не обошлось и без подводных камней. Во-первых, алгоритм работает только с разметчиком Murmur3Partitioner. Если у вас в кластере используется другой разметчик, например, RandomPartitioner, и вы проапгрейдились до 3.0, эта функция не будет работать. Вторая, более распространенная сложность в том, что для использования этой функции при создании кластера с нуля придется постараться. Есть отдельный пост о том, как использовать новый алгоритм распределения токенов с учетом реплик <a href="https://thelastpickle.com/blog/2019/02/21/set-up-a-cluster-with-even-token-distribution.html" target="_blank" rel="nofollow noreferrer noopener">для настройки нового кластера с равномерным распределением токенов</a>.<br /><br />Как видите, в Cassandra 3.0 была предпринята честная попытка сгладить острые углы виртуальных нод. В релизе Cassandra 4.0 появились новые улучшения в этой сфере. Например, в файл <em>cassandra.yaml</em> добавлен новый параметр allocate_tokens_for_local_replication_factorчерез <a href="https://issues.apache.org/jira/browse/CASSANDRA-15260" target="_blank" rel="nofollow noreferrer noopener">CASSANDRA-15260</a>. Как и его двоюродный брат allocate_tokens_for_keyspace, он активирует алгоритм распределения токенов с учетом реплик, если указать для него значение.<br /><br />Но использовать его гораздо проще и приятнее, потому что с ним создание сбалансированного кластера с нуля не требует столько усилий. В простейшем случае достаточно задать значение для allocate_tokens_for_local_replication_factor, а потом просто добавлять ноды. Продвинутые пользователи все еще могут вручную назначать токены для начальных нод, чтобы сохранить желаемый коэффициент репликации. Последующие ноды можно добавлять со значением коэффициента репликации, назначенным параметру allocate_tokens_for_local_replication_factor.<br /><br />Пожалуй, самым ожидаемым и важным изменением в Cassandra 4.0 стало изменение дефолтного значения для параметра num_tokens. Как мы уже говорили, благодаря изменению <a href="https://issues.apache.org/jira/browse/CASSANDRA-13701" target="_blank" rel="nofollow noreferrer noopener">CASSANDRA-13701</a> в Cassandra 4.0 в файле <em>cassandra.yaml</em> для num_tokens установлено значение <strong>16</strong>. Кроме того, параметр allocate_tokens_for_local_replication_factor включен по умолчанию и имеет значение <strong>3</strong>.<br /><br />Эти дефолтные параметры гораздо лучше. В ванильной установке Cassandra 4.0 алгоритм распределения токенов с учетом реплик начинает работать, как только появляется достаточно хостов, чтобы соблюсти коэффициент репликации <strong>3</strong>. В результате имеем равномерное распределение диапазонов токенов для новых нод со всеми преимуществами, которое дает малое число виртуальных нод.<br /><br /><h2 class="t-redactor__h2"><strong>Заключение</strong></h2>Согласованное хэширование и распределение токенов — это основа Cassandra. Благодаря виртуальным нодам с этими важными функциями не придется работать наугад, в частности, изменять размер кластера можно гораздо быстрее и проще. Как правило, чем меньше виртуальных нод, тем менее равномерным будет распределение, поэтому на некоторые ноды ляжет больше нагрузки. Чем больше виртуальных нод, тем больше времени потребуется на операции, охватывающие весь кластер, и тем выше вероятность, что данные будут недоступны при сбое нескольких узлов одновременно. Функции в версии 3.0 и улучшения этих функций в 4.0 позволяют использовать в Cassandra меньше виртуальных нод, но при этом добиться относительно равномерного распределения токенов. В конце концов, новым пользователям будет гораздо удобнее использовать ванильную установку Cassandra 4.0 без дополнительной настройки.<br /><br /></section></div>
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FR: 'Voir également',
DE: 'Siehe auch',
ES: 'Ver también',
PT: 'Veja também',
UK: 'Дивись також',
JA: 'また見なさい',
CN: '也可以看看'
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RU: 'Сегодня',
FR: 'Aujourd\'hui',
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ES: 'Hoy',
PT: 'Hoje',
UK: 'Сьогодні',
JA: '今日',
CN: '今天'
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FR: 'Hier',
DE: 'Gestern',
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PT: 'Ontem',
UK: 'Вчора',
JA: '昨日',
CN: '昨天'
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FR: ['jours'],
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PT: ['dias'],
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RU: 'назад',
FR: 'Il y a',
DE: 'Vor',
ES: 'Hace',
PT: 'Há',
UK: 'тому',
JA: '前',
CN: '前'
};
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DE: ['Januar', 'januar'],
ES: ['Enero', 'de enero'],
PT: ['Janeiro', 'de janeiro'],
UK: ['Січень', 'січня'],
JA: ['一月', '一月'],
CN: ['一月', '一月']
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RU: ['Февраль', 'февраля'],
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DE: ['Februar', 'februar'],
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UK: ['Лютий', 'лютого'],
JA: ['二月', '二月'],
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FR: ['Mars', 'mars'],
DE: ['März', 'märz'],
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PT: ['Março', 'de março'],
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CN: ['三月', '三月']
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RU: ['Апрель', 'апреля'],
FR: ['Avril', 'avril'],
DE: ['April', 'april'],
ES: ['Abril', 'de abril'],
PT: ['Abril', 'de abril'],
UK: ['Квітень', 'квітня'],
JA: ['四月', '四月'],
CN: ['四月', '四月']
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RU: ['Май', 'мая'],
FR: ['Mai', 'mai'],
DE: ['Kann', 'kann'],
ES: ['Mayo', 'de mayo'],
PT: ['Maio', 'de maio'],
UK: ['Травень', 'травня'],
JA: ['五月', '五月'],
CN: ['五月', '五月']
};
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EN: ['June', 'june'],
RU: ['Июнь', 'июня'],
FR: ['Juin', 'juin'],
DE: ['Juni', 'juni'],
ES: ['Junio', 'de junio'],
PT: ['Junho', 'de junho'],
UK: ['Червень', 'червня'],
JA: ['六月', '六月'],
CN: ['六月', '六月']
};
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EN: ['July', 'july'],
RU: ['Июль', 'июля'],
FR: ['Juillet', 'juillet'],
DE: ['Juli', 'Juli'],
ES: ['Julio', 'de julio'],
PT: ['Julho', 'de julho'],
UK: ['Липень', 'липня'],
JA: ['七月', '七月'],
CN: ['七月', '七月']
};
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RU: ['Август', 'августа'],
FR: ['Août', 'août'],
DE: ['August', 'august'],
ES: ['Agosto', 'de agosto'],
PT: ['Agosto', 'de agosto'],
UK: ['Серпень', 'серпня'],
JA: ['八月', '八月'],
CN: ['八月', '八月']
};
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RU: ['Сентябрь', 'сентября'],
FR: ['Septembre', 'septembre'],
DE: ['September', 'september'],
ES: ['Septiembre', 'de septiembre'],
PT: ['Setembro', 'de setembro'],
UK: ['Вересень', 'вересня'],
JA: ['九月', '九月'],
CN: ['九月', '九月']
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RU: ['Октябрь', 'октября'],
FR: ['Octobre', 'octobre'],
DE: ['Oktober', 'oktober'],
ES: ['Octubre', 'de octubre'],
PT: ['Outubro', 'de outubro'],
UK: ['Жовтень', 'жовтня'],
JA: ['十月', '十月'],
CN: ['十月', '十月']
};
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RU: ['Ноябрь', 'ноября'],
FR: ['Novembre', 'novembre'],
DE: ['November', 'november'],
ES: ['Noviembre', 'de noviembre'],
PT: ['Novembro', 'de novembro'],
UK: ['Листопад', 'листопада'],
JA: ['十一月', '十一月'],
CN: ['十一月', '十一月']
};
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RU: ['Декабрь', 'декабря'],
FR: ['Décembre', 'décembre'],
DE: ['Dezember', 'dezember'],
ES: ['Diciembre', 'de diciembre'],
PT: ['Dezembro', 'de dezembro'],
UK: ['Грудень', 'грудня'],
JA: ['十二月', '十二月'],
CN: ['十二月', '十二月']
};
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} else {
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<style>#rec480081308 .t-btnflex.t-btnflex_type_button {color:#ffffff;background-color:#000000;--border-width:0px;border-style:none !important;border-radius:5px;box-shadow:none !important;font-weight:400;transition-duration:0.2s;transition-property: background-color, color, border-color, box-shadow, opacity, transform, gap;transition-timing-function: ease-in-out;}@media (hover: hover) {#rec480081308 .t-btnflex.t-btnflex_type_button:not(.t-animate_no-hover):hover {color:#ffffff !important;background-color:#170f63 !important;}#rec480081308 .t-btnflex.t-btnflex_type_button:not(.t-animate_no-hover):focus-visible {color:#ffffff !important;background-color:#170f63 !important;}}</style></div>
</div>
</div>
<script type="text/javascript">
t_onReady(function () {
t_onFuncLoad('t886_init', function () {
t886_init('480081308');
});
});
</script>
<style>
#rec480081308 .t886__text {
text-align: left;
}
</style>
<style> #rec480081308 .t886__text { font-size: 14px; line-height: 1; color: #000000; }</style>
<style> #rec480081308 .t886__wrapper { border-radius:5px; }</style>
</div>
<div id="rec495453579" class="r t-rec uc-footer--type0" style=" " data-animationappear="off" data-record-type="121" data-alias-record-type="396" >
<!-- T396 -->
<style>#rec495453579 .t396__artboard {height: 847px; background-color: #ffffff; }#rec495453579 .t396__filter {height: 847px; }#rec495453579 .t396__carrier{height: 847px;background-position: center center;background-attachment: scroll;background-size: cover;background-repeat: no-repeat;}@media screen and (max-width: 1199px) {#rec495453579 .t396__artboard,#rec495453579 .t396__filter,#rec495453579 .t396__carrier {height: 840px;}#rec495453579 .t396__filter {}#rec495453579 .t396__carrier {background-attachment: scroll;}}@media screen and (max-width: 959px) {#rec495453579 .t396__artboard,#rec495453579 .t396__filter,#rec495453579 .t396__carrier {height: 1196px;}#rec495453579 .t396__filter {}#rec495453579 .t396__carrier {background-attachment: scroll;}}@media screen and (max-width: 639px) {#rec495453579 .t396__artboard,#rec495453579 .t396__filter,#rec495453579 .t396__carrier {height: 1513px;}#rec495453579 .t396__filter {}#rec495453579 .t396__carrier {background-attachment: scroll;}}@media screen and (max-width: 479px) {#rec495453579 .t396__artboard,#rec495453579 .t396__filter,#rec495453579 .t396__carrier {height: 1536px;}#rec495453579 .t396__filter {}#rec495453579 .t396__carrier {background-attachment: scroll;}}#rec495453579 .tn-elem[data-elem-id="1712236782477"] {
z-index: 3;
top: 74px;;
left: calc(50% - 600px + 20px);;
width: 105px;
height: auto;
}
#rec495453579 .tn-elem[data-elem-id="1712236782477"] .tn-atom {
border-radius: 0px 0px 0px 0px;
background-position: center center;
border-width: var(--t396-borderwidth, 0);
border-style: var(--t396-borderstyle, solid);
border-color: var(--t396-bordercolor, transparent);
transition: background-color var(--t396-speedhover,0s) ease-in-out, color var(--t396-speedhover,0s) ease-in-out, border-color var(--t396-speedhover,0s) ease-in-out, box-shadow var(--t396-shadowshoverspeed,0.2s) ease-in-out;
}
#rec495453579 .tn-elem[data-elem-id="1712236782477"] .tn-atom__img {
border-radius: 0px 0px 0px 0px;
object-position: center center;
}
@media screen and (max-width: 1199px) {
#rec495453579 .tn-elem[data-elem-id="1712236782477"] {
display: table;
left: calc(50% - 480px + 36px);;
height: auto;
}
}
@media screen and (max-width: 959px) {
#rec495453579 .tn-elem[data-elem-id="1712236782477"] {
display: table;
top: 61px;;
left: calc(50% - 320px + 24px);;
height: auto;
}
}
@media screen and (max-width: 639px) {
#rec495453579 .tn-elem[data-elem-id="1712236782477"] {
display: table;
top: 40pxpx;;
left: calc(50% - 240px + 15px);;
width: 105px;
height: auto;
}
}
@media screen and (max-width: 479px) {
#rec495453579 .tn-elem[data-elem-id="1712236782477"] {
display: table;
top: 36px;;
left: calc(50% - 160px + 7px);;
height: auto;
}
}#rec495453579 .tn-elem[data-elem-id="1712235605947"] {
z-index: 3;
top: 74px;;
left: calc(50% - 600px + 20px);;
width: 105px;
height: auto;
}
#rec495453579 .tn-elem[data-elem-id="1712235605947"] .tn-atom {
border-radius: 0px 0px 0px 0px;
opacity: 0;
background-position: center center;
border-width: var(--t396-borderwidth, 0);
border-style: var(--t396-borderstyle, solid);
border-color: var(--t396-bordercolor, transparent);
transition: background-color var(--t396-speedhover,0s) ease-in-out, color var(--t396-speedhover,0s) ease-in-out, border-color var(--t396-speedhover,0s) ease-in-out, box-shadow var(--t396-shadowshoverspeed,0.2s) ease-in-out;
}
#rec495453579 .tn-elem[data-elem-id="1712235605947"] .tn-atom__img {
border-radius: 0px 0px 0px 0px;
object-position: center center;
}
@media screen and (max-width: 1199px) {
#rec495453579 .tn-elem[data-elem-id="1712235605947"] {
display: table;
left: calc(50% - 480px + 36px);;
height: auto;
}
}
@media screen and (max-width: 959px) {
#rec495453579 .tn-elem[data-elem-id="1712235605947"] {
display: table;
top: 61px;;
left: calc(50% - 320px + 24px);;
height: auto;
}
}
@media screen and (max-width: 639px) {
#rec495453579 .tn-elem[data-elem-id="1712235605947"] {
display: table;
top: 40px;;
left: calc(50% - 240px + 15px);;
width: 105px;
height: auto;
}
}
@media screen and (max-width: 479px) {
#rec495453579 .tn-elem[data-elem-id="1712235605947"] {
display: table;
top: 36px;;
left: calc(50% - 160px + 7px);;
height: auto;
}
#rec495453579 .tn-elem[data-elem-id="1712235605947"] .tn-atom {
background-size: cover;
opacity: 0;
}
}#rec495453579 .tn-elem[data-elem-id="1692506348245"] {
z-index: 3;
top: 58px;;
left: calc(50% - 600px + 820px);;
width: 120px;
height: auto;
}
#rec495453579 .tn-elem[data-elem-id="1692506348245"] .tn-atom {
border-radius: 0px 0px 0px 0px;
background-position: center center;
border-width: var(--t396-borderwidth, 0);
border-style: var(--t396-borderstyle, solid);
border-color: var(--t396-bordercolor, transparent);
transition: background-color var(--t396-speedhover,0s) ease-in-out, color var(--t396-speedhover,0s) ease-in-out, border-color var(--t396-speedhover,0s) ease-in-out, box-shadow var(--t396-shadowshoverspeed,0.2s) ease-in-out;
}
#rec495453579 .tn-elem[data-elem-id="1692506348245"] .tn-atom__img {
border-radius: 0px 0px 0px 0px;
object-position: center center;
}
@media screen and (max-width: 1199px) {
#rec495453579 .tn-elem[data-elem-id="1692506348245"] {
display: table;
left: calc(50% - 480px + 640px);;
height: auto;
}
}
@media screen and (max-width: 959px) {
#rec495453579 .tn-elem[data-elem-id="1692506348245"] {
display: table;
top: 755px;;
left: calc(50% - 320px + 24px);;
height: auto;
}
}
@media screen and (max-width: 639px) {
#rec495453579 .tn-elem[data-elem-id="1692506348245"] {
display: table;
top: 835px;;
left: calc(50% - 240px + 20px);;
height: auto;
}
}
@media screen and (max-width: 479px) {
#rec495453579 .tn-elem[data-elem-id="1692506348245"] {
display: table;
top: 863px;;
left: calc(50% - 160px + 10px);;
height: auto;
}
}#rec495453579 .tn-elem[data-elem-id="1692506631214"] {
z-index: 3;
top: 58px;;
left: calc(50% - 600px + 820px);;
width: 120px;
height: auto;
}
#rec495453579 .tn-elem[data-elem-id="1692506631214"] .tn-atom {
border-radius: 0px 0px 0px 0px;
opacity: 0;
background-position: center center;
border-width: var(--t396-borderwidth, 0);
border-style: var(--t396-borderstyle, solid);
border-color: var(--t396-bordercolor, transparent);
transition: background-color var(--t396-speedhover,0s) ease-in-out, color var(--t396-speedhover,0s) ease-in-out, border-color var(--t396-speedhover,0s) ease-in-out, box-shadow var(--t396-shadowshoverspeed,0.2s) ease-in-out;
}
#rec495453579 .tn-elem[data-elem-id="1692506631214"] .tn-atom__img {
border-radius: 0px 0px 0px 0px;
object-position: center center;
}
@media screen and (max-width: 1199px) {
#rec495453579 .tn-elem[data-elem-id="1692506631214"] {
display: table;
left: calc(50% - 480px + 640px);;
height: auto;
}
}
@media screen and (max-width: 959px) {
#rec495453579 .tn-elem[data-elem-id="1692506631214"] {
display: table;
top: 757px;;
left: calc(50% - 320px + 24px);;
height: auto;
}
}
@media screen and (max-width: 639px) {
#rec495453579 .tn-elem[data-elem-id="1692506631214"] {
display: table;
top: 845px;;
left: calc(50% - 240px + 20px);;
height: auto;
}
}
@media screen and (max-width: 479px) {
#rec495453579 .tn-elem[data-elem-id="1692506631214"] {
display: table;
top: 873px;;
left: calc(50% - 160px + 10px);;
height: auto;
}
}#rec495453579 .tn-elem[data-elem-id="1660327289504"] {
color: #8999a9;
z-index: 3;
top: 121px;;
left: calc(50% - 600px + 20px);;
width: 360px;
height: auto;
}
#rec495453579 .tn-elem[data-elem-id="1660327289504"] .tn-atom {
vertical-align: middle;
color: #8999a9;
font-size: 18px;
font-family: var(--t-text-font,Arial);
line-height: 1.33;
font-weight: 400;
background-position: center center;
border-width: var(--t396-borderwidth, 0);
border-style: var(--t396-borderstyle, solid);
border-color: var(--t396-bordercolor, transparent);
transition: background-color var(--t396-speedhover,0s) ease-in-out, color var(--t396-speedhover,0s) ease-in-out, border-color var(--t396-speedhover,0s) ease-in-out, box-shadow var(--t396-shadowshoverspeed,0.2s) ease-in-out;
--t396-shadow-text-opacity: 100%;
text-shadow: var(--t396-shadow-text-x, 0px) var(--t396-shadow-text-y, 0px) var(--t396-shadow-text-blur, 0px) rgba(var(--t396-shadow-text-color), var(--t396-shadow-text-opacity, 100%));
}
@media screen and (max-width: 1199px) {
#rec495453579 .tn-elem[data-elem-id="1660327289504"] {
display: table;
left: calc(50% - 480px + 32px);;
width: 288px;
height: auto;
}
}
@media screen and (max-width: 959px) {
#rec495453579 .tn-elem[data-elem-id="1660327289504"] {
display: table;
top: 68px;;
left: calc(50% - 320px + 153px);;
height: auto;
}
}
@media screen and (max-width: 639px) {
#rec495453579 .tn-elem[data-elem-id="1660327289504"] {
display: table;
top: 81px;;
left: calc(50% - 240px + 20px);;
height: auto;
}
}
@media screen and (max-width: 479px) {
#rec495453579 .tn-elem[data-elem-id="1660327289504"] {
display: table;
left: calc(50% - 160px + 10px);;
width: 300px;
height: auto;
}
#rec495453579 .tn-elem[data-elem-id="1660327289504"] .tn-atom {
font-size: 16px;
line-height: 1.5;
background-size: cover;
}
}#rec495453579 .tn-elem[data-elem-id="1660327420094"] {
color: #172b4d;
z-index: 3;
top: 185px;;
left: calc(50% - 600px + 14px);;
width: 336px;
height: auto;
}
#rec495453579 .tn-elem[data-elem-id="1660327420094"] .tn-atom {
vertical-align: middle;
color: #172b4d;
font-size: 24px;
font-family: var(--t-text-font,Arial);
line-height: 1.08;
font-weight: 400;
background-position: center center;
border-width: var(--t396-borderwidth, 0);
border-style: var(--t396-borderstyle, solid);
border-color: var(--t396-bordercolor, transparent);
transition: background-color var(--t396-speedhover,0s) ease-in-out, color var(--t396-speedhover,0s) ease-in-out, border-color var(--t396-speedhover,0s) ease-in-out, box-shadow var(--t396-shadowshoverspeed,0.2s) ease-in-out;
--t396-shadow-text-opacity: 100%;
text-shadow: var(--t396-shadow-text-x, 0px) var(--t396-shadow-text-y, 0px) var(--t396-shadow-text-blur, 0px) rgba(var(--t396-shadow-text-color), var(--t396-shadow-text-opacity, 100%));
}
@media screen and (max-width: 1199px) {
#rec495453579 .tn-elem[data-elem-id="1660327420094"] {
display: table;
left: calc(50% - 480px + 27px);;
width: 264px;
height: auto;
}
}
@media screen and (max-width: 959px) {
#rec495453579 .tn-elem[data-elem-id="1660327420094"] {
display: table;
top: 124px;;
left: calc(50% - 320px + 20px);;
height: auto;
}
}
@media screen and (max-width: 639px) {
#rec495453579 .tn-elem[data-elem-id="1660327420094"] {
display: table;
left: calc(50% - 240px + 15px);;
width: 440px;
height: auto;
}
}
@media screen and (max-width: 479px) {
#rec495453579 .tn-elem[data-elem-id="1660327420094"] {
display: table;
left: calc(50% - 160px + 5px);;
width: 300px;
height: auto;
}
}#rec495453579 .tn-elem[data-elem-id="1660327526179"] {
color: #172b4d;
z-index: 3;
top: 223px;;
left: calc(50% - 600px + 16px);;
width: 336px;
height: auto;
}
#rec495453579 .tn-elem[data-elem-id="1660327526179"] .tn-atom {
vertical-align: middle;
color: #172b4d;
font-size: 24px;
font-family: var(--t-text-font,Arial);
line-height: 1.08;
font-weight: 400;
background-position: center center;
border-width: var(--t396-borderwidth, 0);
border-style: var(--t396-borderstyle, solid);
border-color: var(--t396-bordercolor, transparent);
transition: background-color var(--t396-speedhover,0s) ease-in-out, color var(--t396-speedhover,0s) ease-in-out, border-color var(--t396-speedhover,0s) ease-in-out, box-shadow var(--t396-shadowshoverspeed,0.2s) ease-in-out;
--t396-shadow-text-opacity: 100%;
text-shadow: var(--t396-shadow-text-x, 0px) var(--t396-shadow-text-y, 0px) var(--t396-shadow-text-blur, 0px) rgba(var(--t396-shadow-text-color), var(--t396-shadow-text-opacity, 100%));
}
@media screen and (max-width: 1199px) {
#rec495453579 .tn-elem[data-elem-id="1660327526179"] {
display: table;
left: calc(50% - 480px + 28px);;
width: 264px;
height: auto;
}
}
@media screen and (max-width: 959px) {
#rec495453579 .tn-elem[data-elem-id="1660327526179"] {
display: table;
top: 162px;;
left: calc(50% - 320px + 20px);;
height: auto;
}
}
@media screen and (max-width: 639px) {
#rec495453579 .tn-elem[data-elem-id="1660327526179"] {
display: table;
left: calc(50% - 240px + 16px);;
width: 440px;
height: auto;
}
}
@media screen and (max-width: 479px) {
#rec495453579 .tn-elem[data-elem-id="1660327526179"] {
display: table;
left: calc(50% - 160px + 6px);;
width: 300px;
height: auto;
}
}#rec495453579 .tn-elem[data-elem-id="1660328247771"] {
color: #172b4d;
z-index: 3;
top: 547px;;
left: calc(50% - 600px + 419px);;
width: 336px;
height: auto;
}
#rec495453579 .tn-elem[data-elem-id="1660328247771"] .tn-atom {
vertical-align: middle;
color: #172b4d;
font-size: 16px;
font-family: var(--t-text-font,Arial);
line-height: 1.5;
font-weight: 400;
background-position: center center;
border-width: var(--t396-borderwidth, 0);
border-style: var(--t396-borderstyle, solid);
border-color: var(--t396-bordercolor, transparent);
transition: background-color var(--t396-speedhover,0s) ease-in-out, color var(--t396-speedhover,0s) ease-in-out, border-color var(--t396-speedhover,0s) ease-in-out, box-shadow var(--t396-shadowshoverspeed,0.2s) ease-in-out;
--t396-shadow-text-opacity: 100%;
text-shadow: var(--t396-shadow-text-x, 0px) var(--t396-shadow-text-y, 0px) var(--t396-shadow-text-blur, 0px) rgba(var(--t396-shadow-text-color), var(--t396-shadow-text-opacity, 100%));
}
@media screen and (max-width: 1199px) {
#rec495453579 .tn-elem[data-elem-id="1660328247771"] {
display: table;
top: 557px;;
left: calc(50% - 480px + 332px);;
width: 264px;
height: auto;
}
}
@media screen and (max-width: 959px) {
#rec495453579 .tn-elem[data-elem-id="1660328247771"] {
display: table;
top: 532px;;
left: calc(50% - 320px + 326px);;
height: auto;
}
}
@media screen and (max-width: 639px) {
#rec495453579 .tn-elem[data-elem-id="1660328247771"] {
display: table;
top: 622px;;
left: calc(50% - 240px + 16px);;
width: 440px;
height: auto;
}
#rec495453579 .tn-elem[data-elem-id="1660328247771"] .tn-atom {
font-size: 15px;
line-height: 1.47;
background-size: cover;
}
}
@media screen and (max-width: 479px) {
#rec495453579 .tn-elem[data-elem-id="1660328247771"] {
display: table;
top: 614px;;
left: calc(50% - 160px + 6px);;
width: 300px;
height: auto;
}
}#rec495453579 .tn-elem[data-elem-id="1660328067115"] {
color: #172b4d;
z-index: 3;
top: 217px;;
left: calc(50% - 600px + 419px);;
width: 336px;
height: auto;
}
#rec495453579 .tn-elem[data-elem-id="1660328067115"] .tn-atom {
vertical-align: middle;
color: #172b4d;
font-size: 16px;
font-family: var(--t-text-font,Arial);
line-height: 1.5;
font-weight: 400;
background-position: center center;
border-width: var(--t396-borderwidth, 0);
border-style: var(--t396-borderstyle, solid);
border-color: var(--t396-bordercolor, transparent);
transition: background-color var(--t396-speedhover,0s) ease-in-out, color var(--t396-speedhover,0s) ease-in-out, border-color var(--t396-speedhover,0s) ease-in-out, box-shadow var(--t396-shadowshoverspeed,0.2s) ease-in-out;
--t396-shadow-text-opacity: 100%;
text-shadow: var(--t396-shadow-text-x, 0px) var(--t396-shadow-text-y, 0px) var(--t396-shadow-text-blur, 0px) rgba(var(--t396-shadow-text-color), var(--t396-shadow-text-opacity, 100%));
}
@media screen and (max-width: 1199px) {
#rec495453579 .tn-elem[data-elem-id="1660328067115"] {
display: table;
top: 219px;;
left: calc(50% - 480px + 332px);;
width: 264px;
height: auto;
}
}
@media screen and (max-width: 959px) {
#rec495453579 .tn-elem[data-elem-id="1660328067115"] {
display: table;
top: 158px;;
left: calc(50% - 320px + 326px);;
height: auto;
}
}
@media screen and (max-width: 639px) {
#rec495453579 .tn-elem[data-elem-id="1660328067115"] {
display: table;
top: 258px;;
left: calc(50% - 240px + 244px);;
width: 212px;
height: auto;
}
#rec495453579 .tn-elem[data-elem-id="1660328067115"] .tn-atom {
font-size: 15px;
line-height: 1.47;
background-size: cover;
}
}
@media screen and (max-width: 479px) {
#rec495453579 .tn-elem[data-elem-id="1660328067115"] {
display: table;
top: 258px;;
left: calc(50% - 160px + 166px);;
width: 140px;
height: auto;
}
}#rec495453579 .tn-elem[data-elem-id="1660328673693"] {
color: #172b4d;
z-index: 3;
top: 229px;;
left: calc(50% - 600px + 816px);;
width: 360px;
height: auto;
}
#rec495453579 .tn-elem[data-elem-id="1660328673693"] .tn-atom {
vertical-align: middle;
color: #172b4d;
font-size: 16px;
font-family: var(--t-text-font,Arial);
line-height: 1.5;
font-weight: 400;
background-position: center center;
border-width: var(--t396-borderwidth, 0);
border-style: var(--t396-borderstyle, solid);
border-color: var(--t396-bordercolor, transparent);
transition: background-color var(--t396-speedhover,0s) ease-in-out, color var(--t396-speedhover,0s) ease-in-out, border-color var(--t396-speedhover,0s) ease-in-out, box-shadow var(--t396-shadowshoverspeed,0.2s) ease-in-out;
--t396-shadow-text-opacity: 100%;
text-shadow: var(--t396-shadow-text-x, 0px) var(--t396-shadow-text-y, 0px) var(--t396-shadow-text-blur, 0px) rgba(var(--t396-shadow-text-color), var(--t396-shadow-text-opacity, 100%));
}
@media screen and (max-width: 1199px) {
#rec495453579 .tn-elem[data-elem-id="1660328673693"] {
display: table;
top: 229px;;
left: calc(50% - 480px + 636px);;
width: 288px;
height: auto;
}
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data-field-left-res-320-value="10" data-field-width-res-320-value="300" data-field-fontsize-res-320-value="16"
data-field-top-res-480-value="81" data-field-left-res-480-value="20"
data-field-top-res-640-value="68" data-field-left-res-640-value="153"
data-field-left-res-960-value="32" data-field-width-res-960-value="288"
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<div class='tn-atom'field='tn_text_1660327289504'>Обучение ИТ-профессионалов</div>
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data-field-top-value="185"
data-field-left-value="14"
data-field-height-value="26" data-field-width-value="336" data-field-axisy-value="top"
data-field-axisx-value="left"
data-field-container-value="grid"
data-field-topunits-value="px"
data-field-leftunits-value="px"
data-field-heightunits-value="px"
data-field-widthunits-value="px"
data-field-textfit-value="autoheight" data-field-fontsize-value="24"
data-field-left-res-320-value="5" data-field-width-res-320-value="300"
data-field-left-res-480-value="15" data-field-width-res-480-value="440"
data-field-top-res-640-value="124" data-field-left-res-640-value="20"
data-field-left-res-960-value="27" data-field-width-res-960-value="264"
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<div class='tn-atom'><a href="tel:+74952480580"rel="nofollow"style="color: inherit">+7 (495) 248-05-80</a></div>
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data-field-top-value="223"
data-field-left-value="16"
data-field-height-value="26" data-field-width-value="336" data-field-axisy-value="top"
data-field-axisx-value="left"
data-field-container-value="grid"
data-field-topunits-value="px"
data-field-leftunits-value="px"
data-field-heightunits-value="px"
data-field-widthunits-value="px"
data-field-textfit-value="autoheight" data-field-fontsize-value="24"
data-field-left-res-320-value="6" data-field-width-res-320-value="300"
data-field-left-res-480-value="16" data-field-width-res-480-value="440"
data-field-top-res-640-value="162" data-field-left-res-640-value="20"
data-field-left-res-960-value="28" data-field-width-res-960-value="264"
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<div class='tn-atom'><a href="mailto:ask@slurm.io"rel="nofollow"style="color: inherit">ask@slurm.io</a></div>
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data-field-top-value="547"
data-field-left-value="419"
data-field-height-value="24" data-field-width-value="336" data-field-axisy-value="top"
data-field-axisx-value="left"
data-field-container-value="grid"
data-field-topunits-value="px"
data-field-leftunits-value="px"
data-field-heightunits-value="px"
data-field-widthunits-value="px"
data-field-textfit-value="autoheight" data-field-fontsize-value="16"
data-field-top-res-320-value="614" data-field-left-res-320-value="6" data-field-width-res-320-value="300"
data-field-top-res-480-value="622" data-field-left-res-480-value="16" data-field-width-res-480-value="440" data-field-fontsize-res-480-value="15"
data-field-top-res-640-value="532" data-field-left-res-640-value="326"
data-field-top-res-960-value="557" data-field-left-res-960-value="332" data-field-width-res-960-value="264"
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<div class='tn-atom'><a href="/corporate"style="color: inherit">Корпоративное обучение</a></div>
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data-field-top-value="217"
data-field-left-value="419"
data-field-height-value="24" data-field-width-value="336" data-field-axisy-value="top"
data-field-axisx-value="left"
data-field-container-value="grid"
data-field-topunits-value="px"
data-field-leftunits-value="px"
data-field-heightunits-value="px"
data-field-widthunits-value="px"
data-field-textfit-value="autoheight" data-field-fontsize-value="16"
data-field-top-res-320-value="258" data-field-left-res-320-value="166" data-field-width-res-320-value="140"
data-field-top-res-480-value="258" data-field-left-res-480-value="244" data-field-width-res-480-value="212" data-field-fontsize-res-480-value="15"
data-field-top-res-640-value="158" data-field-left-res-640-value="326"
data-field-top-res-960-value="219" data-field-left-res-960-value="332" data-field-width-res-960-value="264"
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<div class='tn-atom'><a href="/calendar"style="color: inherit">Календарь</a></div>
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<div class='t396__elem tn-elem uc-footer-menu--partner tn-elem__4954535791660328673693' data-elem-id='1660328673693' data-elem-type='text'
data-field-top-value="229"
data-field-left-value="816"
data-field-height-value="48" data-field-width-value="360" data-field-axisy-value="top"
data-field-axisx-value="left"
data-field-container-value="grid"
data-field-topunits-value="px"
data-field-leftunits-value="px"
data-field-heightunits-value="px"
data-field-widthunits-value="px"
data-field-textfit-value="autoheight" data-field-fontsize-value="16"
data-field-top-res-320-value="1017" data-field-left-res-320-value="9" data-field-width-res-320-value="300"
data-field-top-res-480-value="1008" data-field-left-res-480-value="20" data-field-width-res-480-value="440" data-field-fontsize-res-480-value="15"
data-field-top-res-640-value="874" data-field-left-res-640-value="20" data-field-width-res-640-value="256"
data-field-top-res-960-value="229" data-field-left-res-960-value="636" data-field-width-res-960-value="288"
>
<div class='tn-atom'><a href="https://southbridge.io/?utm_source=slurm&utm_medium=footer"rel="nofollow"style="color: inherit"><span style="font-weight: 700;">Southbridge.</span> DevOps-аутсорсер, поддержка высоконагруженных проектов.</a></div>
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data-field-top-value="305"
data-field-left-value="16"
data-field-height-value="24" data-field-width-value="336" data-field-axisy-value="top"
data-field-axisx-value="left"
data-field-container-value="grid"
data-field-topunits-value="px"
data-field-leftunits-value="px"
data-field-heightunits-value="px"
data-field-widthunits-value="px"
data-field-textfit-value="autoheight" data-field-fontsize-value="16"
data-field-left-res-320-value="6" data-field-width-res-320-value="140"
data-field-top-res-480-value="258" data-field-left-res-480-value="16" data-field-width-res-480-value="212" data-field-fontsize-res-480-value="15"
data-field-top-res-640-value="246" data-field-left-res-640-value="20"
data-field-top-res-960-value="315" data-field-left-res-960-value="28" data-field-width-res-960-value="264"
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<div class='tn-atom'><a href="https://habr.com/ru/companies/slurm/articles/"rel="nofollow"style="color: inherit">Хабр</a></div>
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data-field-top-value="273"
data-field-left-value="16"
data-field-height-value="24" data-field-width-value="336" data-field-axisy-value="top"
data-field-axisx-value="left"
data-field-container-value="grid"
data-field-topunits-value="px"
data-field-leftunits-value="px"
data-field-heightunits-value="px"
data-field-widthunits-value="px"
data-field-textfit-value="autoheight" data-field-fontsize-value="16"
data-field-left-res-320-value="6" data-field-width-res-320-value="140"
data-field-top-res-480-value="220" data-field-left-res-480-value="16" data-field-width-res-480-value="212" data-field-fontsize-res-480-value="15"
data-field-top-res-640-value="212" data-field-left-res-640-value="20"
data-field-top-res-960-value="281" data-field-left-res-960-value="28" data-field-width-res-960-value="264"
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<div class='tn-atom'><a href="https://slurm.mave.digital/"rel="nofollow"style="color: inherit">Подкаст</a></div>
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data-field-top-value="274"
data-field-left-value="8"
data-field-height-value="24" data-field-width-value="9" data-field-axisy-value="top"
data-field-axisx-value="left"
data-field-container-value="grid"
data-field-topunits-value="px"
data-field-leftunits-value="px"
data-field-heightunits-value="px"
data-field-widthunits-value="px"
data-field-textfit-value="autoheight" data-field-fontsize-value="16"
data-field-top-res-320-value="218" data-field-left-res-320-value="0"
data-field-top-res-480-value="222" data-field-left-res-480-value="8" data-field-fontsize-res-480-value="15"
data-field-top-res-640-value="211" data-field-left-res-640-value="10"
data-field-top-res-960-value="283" data-field-left-res-960-value="20"
>
<div class='tn-atom'field='tn_text_1660728533851'>•</div>
</div>
<div class='t396__elem tn-elem uc-footer-menu tn-elem__4954535791660328247775' data-elem-id='1660328247775' data-elem-type='text'
data-field-top-value="579"
data-field-left-value="419"
data-field-height-value="24" data-field-width-value="336" data-field-axisy-value="top"
data-field-axisx-value="left"
data-field-container-value="grid"
data-field-topunits-value="px"
data-field-leftunits-value="px"
data-field-heightunits-value="px"
data-field-widthunits-value="px"
data-field-textfit-value="autoheight" data-field-fontsize-value="16"
data-field-top-res-320-value="652" data-field-left-res-320-value="6" data-field-width-res-320-value="300"
data-field-top-res-480-value="660" data-field-left-res-480-value="16" data-field-width-res-480-value="440" data-field-fontsize-res-480-value="15"
data-field-top-res-640-value="566" data-field-left-res-640-value="326"
data-field-top-res-960-value="591" data-field-left-res-960-value="332" data-field-width-res-960-value="264"
>
<div class='tn-atom'><a href="/universal-tickets"style="color: inherit">Универсальные доступы</a></div>
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<div class='t396__elem tn-elem uc-footer-menu tn-elem__4954535791660328067118' data-elem-id='1660328067118' data-elem-type='text'
data-field-top-value="185"
data-field-left-value="419"
data-field-height-value="24" data-field-width-value="336" data-field-axisy-value="top"
data-field-axisx-value="left"
data-field-container-value="grid"
data-field-topunits-value="px"
data-field-leftunits-value="px"
data-field-heightunits-value="px"
data-field-widthunits-value="px"
data-field-textfit-value="autoheight" data-field-fontsize-value="16"
data-field-top-res-320-value="220" data-field-left-res-320-value="166" data-field-width-res-320-value="140"
data-field-top-res-480-value="220" data-field-left-res-480-value="244" data-field-width-res-480-value="212" data-field-fontsize-res-480-value="15"
data-field-top-res-640-value="124" data-field-left-res-640-value="326"
data-field-top-res-960-value="185" data-field-left-res-960-value="332" data-field-width-res-960-value="264"
>
<div class='tn-atom'><a href="/catalog"style="color: inherit">Все курсы</a></div>
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data-field-top-value="611"
data-field-left-value="419"
data-field-height-value="24" data-field-width-value="336" data-field-axisy-value="top"
data-field-axisx-value="left"
data-field-container-value="grid"
data-field-topunits-value="px"
data-field-leftunits-value="px"
data-field-heightunits-value="px"
data-field-widthunits-value="px"
data-field-textfit-value="autoheight" data-field-fontsize-value="16"
data-field-top-res-320-value="690" data-field-left-res-320-value="6" data-field-width-res-320-value="300"
data-field-top-res-480-value="698" data-field-left-res-480-value="16" data-field-width-res-480-value="440" data-field-fontsize-res-480-value="15"
data-field-top-res-640-value="600" data-field-left-res-640-value="326"
data-field-top-res-960-value="625" data-field-left-res-960-value="332" data-field-width-res-960-value="264"
>
<div class='tn-atom'><a href="/faq-for-oformitel"style="color: inherit">Оплата курса от компании</a></div>
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<div class='t396__elem tn-elem uc-footer-menu tn-elem__4954535791660328067120' data-elem-id='1660328067120' data-elem-type='text'
data-field-top-value="249"
data-field-left-value="419"
data-field-height-value="24" data-field-width-value="336" data-field-axisy-value="top"
data-field-axisx-value="left"
data-field-container-value="grid"
data-field-topunits-value="px"
data-field-leftunits-value="px"
data-field-heightunits-value="px"
data-field-widthunits-value="px"
data-field-textfit-value="autoheight" data-field-fontsize-value="16"
data-field-top-res-320-value="296" data-field-left-res-320-value="166" data-field-width-res-320-value="140"
data-field-top-res-480-value="296" data-field-left-res-480-value="244" data-field-width-res-480-value="212" data-field-fontsize-res-480-value="15"
data-field-top-res-640-value="192" data-field-left-res-640-value="326"
data-field-top-res-960-value="253" data-field-left-res-960-value="332" data-field-width-res-960-value="264"
>
<div class='tn-atom'><a href="/free"style="color: inherit">Бесплатные материалы</a></div>
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data-field-top-value="337"
data-field-left-value="16"
data-field-height-value="24" data-field-width-value="336" data-field-axisy-value="top"
data-field-axisx-value="left"
data-field-container-value="grid"
data-field-topunits-value="px"
data-field-leftunits-value="px"
data-field-heightunits-value="px"
data-field-widthunits-value="px"
data-field-textfit-value="autoheight" data-field-fontsize-value="16"
data-field-left-res-320-value="6" data-field-width-res-320-value="140"
data-field-top-res-480-value="296" data-field-left-res-480-value="16" data-field-width-res-480-value="212" data-field-fontsize-res-480-value="15"
data-field-top-res-640-value="280" data-field-left-res-640-value="20"
data-field-top-res-960-value="349" data-field-left-res-960-value="28" data-field-width-res-960-value="264"
>
<div class='tn-atom'><a href="https://t.me/slurmnews"style="color: inherit">Telegram</a></div>
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<div class='t396__elem tn-elem uc-footer-menu tn-elem__4954535791660328067122' data-elem-id='1660328067122' data-elem-type='text'
data-field-top-value="281"
data-field-left-value="419"
data-field-height-value="24" data-field-width-value="336" data-field-axisy-value="top"
data-field-axisx-value="left"
data-field-container-value="grid"
data-field-topunits-value="px"
data-field-leftunits-value="px"
data-field-heightunits-value="px"
data-field-widthunits-value="px"
data-field-textfit-value="autoheight" data-field-fontsize-value="16"
data-field-top-res-320-value="344" data-field-left-res-320-value="166" data-field-width-res-320-value="140"
data-field-top-res-480-value="334" data-field-left-res-480-value="244" data-field-width-res-480-value="212" data-field-fontsize-res-480-value="15"
data-field-top-res-640-value="226" data-field-left-res-640-value="326"
data-field-top-res-960-value="287" data-field-left-res-960-value="332" data-field-width-res-960-value="264"
>
<div class='tn-atom'><a href="/speaker"style="color: inherit">Спикеры</a></div>
</div>
<div class='t396__elem tn-elem uc-footer-menu tn-elem__4954535791664355590156' data-elem-id='1664355590156' data-elem-type='text'
data-field-top-value="313"
data-field-left-value="419"
data-field-height-value="24" data-field-width-value="336" data-field-axisy-value="top"
data-field-axisx-value="left"
data-field-container-value="grid"
data-field-topunits-value="px"
data-field-leftunits-value="px"
data-field-heightunits-value="px"
data-field-widthunits-value="px"
data-field-textfit-value="autoheight" data-field-fontsize-value="16"
data-field-top-res-320-value="382" data-field-left-res-320-value="166" data-field-width-res-320-value="140"
data-field-top-res-480-value="372" data-field-left-res-480-value="244" data-field-width-res-480-value="212" data-field-fontsize-res-480-value="15"
data-field-top-res-640-value="260" data-field-left-res-640-value="326"
data-field-top-res-960-value="321" data-field-left-res-960-value="332" data-field-width-res-960-value="264"
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<div class='tn-atom'><a href="/for-speakers"style="color: inherit">Для спикеров</a></div>
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<div class='t396__elem tn-elem uc-footer-menu tn-elem__4954535791738909171549' data-elem-id='1738909171549' data-elem-type='text'
data-field-top-value="345"
data-field-left-value="419"
data-field-height-value="24" data-field-width-value="336" data-field-axisy-value="top"
data-field-axisx-value="left"
data-field-container-value="grid"
data-field-topunits-value="px"
data-field-leftunits-value="px"
data-field-heightunits-value="px"
data-field-widthunits-value="px"
data-field-textfit-value="autoheight" data-field-fontsize-value="16"
data-field-top-res-320-value="420" data-field-left-res-320-value="166" data-field-width-res-320-value="140"
data-field-top-res-480-value="410" data-field-left-res-480-value="244" data-field-width-res-480-value="212" data-field-fontsize-res-480-value="15"
data-field-top-res-640-value="294" data-field-left-res-640-value="326"
data-field-top-res-960-value="355" data-field-left-res-960-value="332" data-field-width-res-960-value="264"
>
<div class='tn-atom'><a href="https://slurm.io/careers"style="color: inherit">Работа в Слёрме</a></div>
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<div class='t396__elem tn-elem tn-elem__4954535791660328170303' data-elem-id='1660328170303' data-elem-type='text'
data-field-top-value="503"
data-field-left-value="419"
data-field-height-value="24" data-field-width-value="336" data-field-axisy-value="top"
data-field-axisx-value="left"
data-field-container-value="grid"
data-field-topunits-value="px"
data-field-leftunits-value="px"
data-field-heightunits-value="px"
data-field-widthunits-value="px"
data-field-textfit-value="autoheight" data-field-fontsize-value="18"
data-field-top-res-320-value="570" data-field-left-res-320-value="9" data-field-width-res-320-value="300" data-field-fontsize-res-320-value="16"
data-field-top-res-480-value="578" data-field-left-res-480-value="16" data-field-width-res-480-value="440"
data-field-top-res-640-value="488" data-field-left-res-640-value="326"
data-field-top-res-960-value="513" data-field-left-res-960-value="332" data-field-width-res-960-value="264"
>
<div class='tn-atom'field='tn_text_1660328170303'>Корпоративным клиентам</div>
</div>
<div class='t396__elem tn-elem tn-elem__4954535791660328581896' data-elem-id='1660328581896' data-elem-type='text'
data-field-top-value="185"
data-field-left-value="820"
data-field-height-value="24" data-field-width-value="360" data-field-axisy-value="top"
data-field-axisx-value="left"
data-field-container-value="grid"
data-field-topunits-value="px"
data-field-leftunits-value="px"
data-field-heightunits-value="px"
data-field-widthunits-value="px"
data-field-textfit-value="autoheight" data-field-fontsize-value="18"
data-field-top-res-320-value="973" data-field-left-res-320-value="12" data-field-width-res-320-value="300" data-field-fontsize-res-320-value="16"
data-field-top-res-480-value="964" data-field-left-res-480-value="20" data-field-width-res-480-value="440"
data-field-top-res-640-value="830" data-field-left-res-640-value="24" data-field-width-res-640-value="288"
data-field-left-res-960-value="640" data-field-width-res-960-value="288"
>
<div class='tn-atom'field='tn_text_1660328581896'>Партнёры</div>
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<div class='t396__elem tn-elem tn-elem__4954535791660328396738' data-elem-id='1660328396738' data-elem-type='text'
data-field-top-value="736"
data-field-left-value="20"
data-field-height-value="24" data-field-width-value="360" data-field-axisy-value="top"
data-field-axisx-value="left"
data-field-container-value="grid"
data-field-topunits-value="px"
data-field-leftunits-value="px"
data-field-heightunits-value="px"
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