Parseable

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Debugging distributed systems usually means switching between 4 different dashboards. We just shipped Insights in Traces to fix that. Here's what it looks like

Query performance: 𝗦𝗮𝗺𝗲 𝗹𝗲𝗮𝗴𝘂𝗲 𝗮𝘀 𝘁𝗵𝗲 𝗯𝗲𝘀𝘁 𝗢𝗟𝗔𝗣 𝗱𝗮𝘁𝗮𝗯𝗮𝘀𝗲𝘀. Parseable sits at ×2.97 relative query time, right alongside ClickHouse (×2.56) and DuckDB (×1.98). Being in the same league as analytical databases while also delivering the best compression and a full observability stack, that's best of both worlds. Full results: logg.ing/clickbench

We've been heads-down building Parseable core - the observability datalake for AI era. We recently benchmarked Parseable on ClickBench to understand the performance characteristics. Here are the results. Compression: #1 on ClickBench. 𝗣𝗮𝗿𝘀𝗲𝗮𝗯𝗹𝗲 𝗮𝗰𝗵𝗶𝗲𝘃𝗲𝘀 𝘁𝗵𝗲 𝗯𝗲𝘀𝘁 𝗰𝗼𝗺𝗽𝗿𝗲𝘀𝘀𝗶𝗼𝗻 𝗿𝗮𝘁𝗶𝗼 at 13.06 GiB, ahead of ClickHouse (13.73 GiB) and nearly 6× better than Elasticsearch (79.96 GiB). Compression is a design outcome. In observability, volumes drive the cost structurally. When you're ingesting petabytes of logs, metrics, and traces, the compression advantage compounds into massive savings. Best compression = most cost-effective solution. #Observability #LogManagement #ClickBench #DataEngineering #Parquet #CostOptimization #DevOps #SRE #Monitoring #Analytics

Finding the needle in a haystack of telemetry data? Filters are everything. Based on our users feedback, we just shipped new filters in Parseable to help you zero in faster. Check it out today at telemetry.new

We recently took some time off from building and shipping stuff to celebrate, recharge, and just enjoy each other's company outside of Slack threads and standups. Here's a little glimpse of Team Parseable out of office

Introducing our new 𝗧𝗿𝗮𝗰𝗲 𝗩𝗶𝗲𝘄. We built this to give you complete visibility into the lifecycle of your requests, but it goes beyond just standard debugging. As we move toward 𝗔𝗴𝗲𝗻𝘁𝗶𝗰 𝗢𝗯𝘀𝗲𝗿𝘃𝗮𝗯𝗶𝗹𝗶𝘁𝘆, traces are becoming the critical "X-ray" for AI. They allow you to map the non-deterministic "thought process" of your agents, visualizing every decision node, tool use, and LLM interaction in a clear waterfall view.

We are in the age of coding agents, which means effective monitoring has never been more critical. The problem? The current stack is fragmented. Evals stay in pre-production while agent monitoring sits in production, and both are often isolated from your general-purpose observability tools. This disconnection makes it incredibly difficult to understand the root cause when things go wrong. We wrote a comprehensive guide on how to instrument your coding agents to move beyond the "black box" and bridge these silos. Read the detailed blog post: parseable.com/blog/monitorin…

Happy Thanksgiving 🔥🦃 from the entire Parseable team! We are incredibly grateful for our community, our users, and the ecosystem that helps us grow every day. We hope your day is filled with high availability of food and zero downtime with family and friends. 🥧

We absolutely loved the energy at #KubeCon NA this year. One of the highlights was our raffle for the Meta Ray-Ban smart glasses for our new social followers. Look what just arrived in the mail for our winner, Žilvinas Urbonas 🎁 We hope you enjoy the new specs, Žilvinas! Thanks for stopping by our booth. Thanks to everyone who participated. Stay tuned to our page for more updates, product news, and future giveaways!