Timescale Newsletter Roundup: January 2022

Timescale Newsletter Roundup: 
January 2022

Welcome to the first newsletter roundup of 2022! 🥳 We hope you had a safe and happy holiday season! The Timescale Team had a wonderful time – our company Slack was inundated with recipes 🥞, movie and book recommendations, and lots of skiing 🏔.

We’re back full of energy for the new year, with many product launches and exciting announcements on the horizon.

We’re on a mission to teach the world about time-series data, supporting and growing communities around the world. And, sharing educational resources as broadly as possible is one way to do just that :).

Here’s a snapshot of the content we shared with our readers this month (subscribe to get updates straight to your inbox).

Product updates & announcements

timescale/promscale GitHub
timescale/promscale GitHub

Promscale 0.8  🚀 A new version of Promcale was released in January. This release includes new features that make trace data management easier, giving users the ability to configure the retention period for tracing data in Promscale and deleting all their tracing data easier. This release also comes with improved CLI flags, new extension packages for Linux, additional instrumentation, and the ability to configure the <default_chunk_interval> in Promscale.

New Promscale docs Right before the holidays, we gave some 💛 to our Promscale documentation, adding more general information about Promscale and tobs, and instructions on how to ingest, query, and visualize data with Promscale.

New install docs – We recently updated our “Install TimescaleDB” instructions. You will now find information on how to install TimescaleDB in a self-hosted manner, through pre-built containers, and pre-built cloud images as well as new instructions on how to sign up for Timescale Cloud and Manage Service for TimescaleDB, our two hosted options.

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We also wanted to give a shoutout to our friends at Jaeger for including a contribution from Mat Arye, our Observability Team Lead, in the latest Jager release! The support for a remote gRPC storage plugin in Jaeger will make it easier on only to use Promscale, but also for other observability solutions. Big thank you to the Jaeger team!

New technical content, videos & tutorials

General concepts time_bucket() and time_bucket_gapfill() functionsWatch Timescale team members Miranda Auhl and David Kohn dive into the time_bucket() and time_bucket_gapfill functions and explore what it is, how to use them, and how it works!

Get your finances together with PythonWatch Attila Toth´s session from Pyjamas Conference 2021 that took place on December 4, 2021.

Analyzing Wordle data from Twitter using PostgreSQL and TimescaleDBIn this live stream recording, Timescale Developer Advocate Ryan Booz and Timescale Engineer David Kohn play around with Wordle data taken from Twitter.

Visualize time-series data with TimescaleDB and Apache SupersetDid you know you can use TimescaleDB as a backend for Apache Superset? Learn how to create fast dashboards using TimescaleDB continuous aggregates and how to use TimescaleDB functions with/inside Superset (e.g., time_bucket, first/last, other hyperfunctions).

New #remote-friendly events & community

VirtualTimescale virtual monthly Office Hours (Feb 1)

If you haven’t joined our monthly sessions yet, now’s your chance! Office Hours are always different, topics ranging from best ways to integrate with third-party tools to musings on open-source technology. No matter what, they are always chock-full of expert advice, community projects... and fun!

💬 If you can’t join but have a question, reach out to our engineering team on Slack!

Webinar Postgres Conference Webinar Series (Feb 1)

Timescale Developer Advocate Ryan Booz will be giving a virtual talk on how to best use TimescaleDB for the most demanding time-series workloads, demoing features like native compression, continuous aggregates, specialized analytics functions, query planner enhancements - in essence, all the TimescaleDB goodness!

Virtual – DoKC Talks: What more can I learn from my OpenTelemetry traces? (Feb 1)

We join our friends from Data on Kubernetes Community to talk about distributed tracing! In this meetup, Promscale Engineer John Pruitt will show you how to use SQL queries to build awesome Grafana dashboards 🔥 for your traces.

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If you cannot attend this meetup but you still want to ask John any questions on OpenTelemetry traces, he will also be in FOSDEM during the weekend! Keep scrolling for more info. ✨

Virtual – FOSDEM ‘22 (Feb 5-6)

Hear from Timescale team members at FOSDEM ‘22. Here’s more information on their sessions:

TimescaleDB tips, reading list & more

How to store and analyze NFT data in a relational database – In this post, we share the technical insights we gained from designing and building the Timescale NFT Starter Kit. If you are interested in tracking and analyzing NFT transactional data, this post is for you!

A different and (often) better way to downsample your Prometheus metrics – A better option for downsampling Prometheus metrics, enabling developers to do accurate and flexible trend analysis on those metrics over long periods of time with high performance and reduced storage costs.

Generating sample time-series data three-part series Learn how to quickly create recurring time-series data for charting and testing PostgreSQL and TimescaleDB functions.

Part 1: How to create (lots!) of sample time-series data with PostgreSQL generate_series()

Part 2: Generating more realistic sample time-series data with PostgreSQL

Part 3: How to shape sample data with PostgreSQL generate_series() and SQL

Community contributions

How to run SQL commands in a PostgreSQL Docker container? – This article will explain how to run your arbitrary SQL commands against a PostgreSQL database running in a Docker container on Windows.

Building a cryptocurrency site with Svelte, Python, and TimescaleDB – Great engineering blog post from Trading Strategy - Enabling non-custodial trading across Uniswap Labs compatible exchanges (Ethereum, Binance, Polygon) powered by TimescaleDB for its real-time APIs.

Collecting system information from a bunch of Kubernetes clustersPavel Golovin, Software Engineer at Flant, shares his journey to get an overall state of K8s clusters started from a simple Bash script. Today, Flant makes Python-based data analytics using data from Promscale connected to Grafana Agent.

Wrapping Up

And, that concludes this month’s newsletter roundup. We’ll continue to release new content, events, and more - posting monthly updates for everyone.

If you’d like to get updates as soon as they’re available, subscribe to our newsletter (2x monthly emails, prepared with 💛 and no fluff or jargon, promise).

Happy building!

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