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6 posts tagged with "Observability"

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· 5 min read

We released pb, a modern, fast and intuitive CLI for log management couple of months ago. pb is built for developers who like the comfort of their terminal. Log data is primarily textual, and hence it was important that pb is pluggable via the linux pipe | to other text manipulation tools like grep, awk, sed etc.

In this post, we will see how pb can be used to wrangle log data in the terminal. We'll also explore the new pb tail command to see how it can be used to tail logs in the terminal.

· 5 min read
Aldrin Jenson

Engineers often run into the issue of reproducibility of an issue. Something that happens at one location is hard to reproduce at another location. More often so, for SREs and DevOps folks whose jobs revolve around several moving parts.

Folks at Fiberplane saw this problem and decided to solve it. Fiberplane provides collaborative notebooks for incident debugging, post-mortem, runbooks and general DevOps debugging. Much like Jupyter Notebooks, Fiberplane allows creating a single interface that let's users interact with a wide variety of observability tools and build shareable notebooks, via a highly extensible plugin system.

In this blog post, we'll delve into Fiberplane and explore the synergistic power of using Parseable as a data provider within the Fiberplane ecosystem.

· 3 min read

pb is a command line tool designed to fit developer's toolkit and help debug issues faster. You can point pb to a Parseable for instance, query and analyze logs, directly from the comfort of command line. The focus is to meet the users where they are, and not force them to switch contexts into different dashboards. pb is written in Go and available as a single static binary for all the major platforms.

· 6 min read

AWS Lambda is a serverless compute service that allows you to run code in response to certain events. However, debugging, monitoring or audit logs of Lambda functions are tightly coupled to AWS CloudWatch, which is a leading cost driver for Enterprises. In this post, we will see how to use Parseable to ingest logs and store them in a cost effective manner on AWS S3 for longer and more meaningful analytics.

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