Remove technologies elasticsearch-monitoring
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Ensuring the Successful Launch of Ads on Netflix

The Netflix TechBlog

In this blog post, we’ll discuss the methods we used to ensure a successful launch, including: How we tested the system Netflix technologies involved Best practices we developed Realistic Test Traffic Netflix traffic ebbs and flows throughout the day in a sinusoidal pattern. We used Elasticsearch dashboards to analyze results.

Traffic 342
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Are Times still Good for Load Testing?

Alex Podelko

Another trend is to integrate them with other products to provide needed functionality – such as monitoring, analysis, and reporting. Often they get integrated with the TICK stack (Telegraf, InfluxDB, Chronohraf, Kapasitor) , the ELK stack (Elasticsearch, Logstash, Kibana) , Prometheus , and Grafana. Any thoughts?

Testing 243
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Extend the AI and automation core of Dynatrace with custom plugins

Dynatrace

For full-stack monitoring, you need 360-degree visibility from each customer’s initial interaction with your applications, through the entire request call sequence, down to containers, infrastructure, and cloud. Monitor and analyze any remote technology with ActiveGate plugins. Dynatrace news.

Java 36
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How Netflix Content Engineering makes a federated graph searchable

The Netflix TechBlog

Using the type information present in the GraphQL query template and the user specified index configuration we were able to create an index template with a set of custom Elasticsearch text analyzers that generalized well across domains. By transacting with a database which is monitored by a CDC connector that creates events, or b.

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Dynatrace Managed turnkey Premium High Availability for globally distributed data centers (Early Adopter)

Dynatrace

We’re therefore proud to announce Premium High Availability for Dynatrace Managed to address exactly this need in a completely turnkey manner without any external load balancing or replication technologies. Near-zero RPO and RTO—monitoring continues seamlessly and without data loss in failover scenarios.

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Data Mesh?—?A Data Movement and Processing Platform @ Netflix

The Netflix TechBlog

A Data Movement and Processing Platform @ Netflix By Bo Lei , Guilherme Pires , James Shao , Kasturi Chatterjee , Sujay Jain , Vlad Sydorenko Background Realtime processing technologies (A.K.A It monitors the source database’s bin log and produces CDC events to the Data Mesh source fronting Kafka topic.

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Unlock the observability value of log data with processing at scale

Dynatrace

In this example, FILTER_OUT() is used to drop all logs where the duration of the call is under 100 ms: PARSE(content, "LD 'My monitored service call took ' INT:duration 'ms'"). The new attribute batchjobs.time can then be converted into a metric for monitoring. FILTER_OUT(duration < 100). time + batchjob2.time)).