Operations | Monitoring | ITSM | DevOps | Cloud

I’d like to share some of the best practices we’ve learned on our journey to battle performance issues with the Jaeger tracing tool. Some may say we are experts in logging. We log for a living, and have our log analytics service (which we based on open source ELK Stack) to prove it. We’ve mastered logging to the level where debugging and troubleshooting our system is a no-brainer.

Elastic is prepping for Elasticsearch 8.0, but in the meantime is rolling out upgrades and features with Elasticsearch 7.7. The new version introduces asynchronous search as well as changes with Elasticsearch clusters, mapping, SQL enhancements, snapshots and machine learning. This post will cover just a few of the highlights of the new release. Besides asynchronous search, ES 7.7 also introduces multi-class classification, reduced heap usage, inference time features, and better password security.

Last week, the first OpenObservability conference took place. This event had amazing content contributions from open source project leaders, users, and influencers. We’ve seen massive growth and adoption in the open source observability space from the inspiring work being done across tracing, logging, and especially metrics. The new data stores and capabilities are growing at breakneck speed. There are more choices— yet more complexity—than ever before.

Current cloud investments have been a boost for flexibility and productivity. The challenge is that there is a single point of failure with these platforms, requiring diversity of providers to reduce dependencies. The future of cloud computing will see effects from the ambitions and expansion of cloud providers themselves, as well as potential competition. This is especially true with Amazon, Google, and to a lesser extent Microsoft.