Elastic made their latest minor Elasticsearch release on May 25, 2021. Elasticsearch Version 7.13 contains the rollout of several features that were only in preview in earlier versions. There are also enhancements to existing features, critical bug fixes, and some breaking changes of note. Three more patches have been released on the minor version, and more are expected before releasing the next minor version.
It’s been an exciting year here at Coralogix. We welcomed our 2,000th customer (more than doubling our customer base) and almost tripled our revenue. We also announced our Series B Funding and started to scale our R&D teams and go-to-market strategy. Most exciting, though, was last September when we launched Streamaⓒ – our stateful streaming analytics pipeline. And the excitement continues!
There’s an insidious disease increasingly afflicting DevOps teams. It begins innocuously. A team member suggests adding a new logging tool. The senior dev decides to upgrade the tooling. Then it bites. You’re spending more time navigating between windows than writing code. You’re scared to make an upgrade because it might break the toolchain. The disease is tool sprawl.
AIOps is a DevOps strategy that brings the power of machine learning to bear on observability and system management. It’s not surprising that an increasing number of companies are now adopting this approach. AIOps first came onto the scene in 2015 (coincidentally the same year as Coralogix) and has been gaining momentum for the past half-decade. In this post, we’ll talk about what AIOps is, and why a business might want to use it for their log analytics.
Elasticsearch is a distributed search and analytics engine used for real-time data processing of several different data types. Elasticsearch has built-in processing for numerical, geospatial, and structured text values. Unstructured text values have some built-in analytics capabilities, but custom text fields generally require custom analysis. Built-in text analysis uses analyzers provided by Elasticsearch, but customization is also possible.
Azure, AWS, and GCP cloud services are invaluable to their enterprise customers. When providers like Microsoft are hit with DNS issues or other errors that lead to downtime, it has huge ramifications for their users. The recent Azure cloud services outage was a good example of that. In this post, we’ll look at that outage and examine what it can teach us about enterprise cloud services and how we can reduce risk for our own applications.
President Joe Biden recently signed an executive order which made adhering to cybersecurity standards a legal requirement for federal departments and agencies. The move was not a surprise. It comes after a string of high-profile cyber-attacks and data breaches in 2020 and 2021. The frequency and scale of these events exposed a clear culture of lax cybersecurity practices throughout both the public and private sectors.
When building a microservices system, configuring events to trigger additional logic using an event stream is highly valuable. One common use case is receiving notifications when errors are seen in one of your APIs. Ideally, when errors occur at a specific rate or frequency, you want your system to detect that and send your DevOps team a notification. Since AWS APIs often use stateless functions like Lambdas, you need to include a tracking mechanism to send these notifications manually.
