Earlier this month, Ivana Huckova, one of Grafana’s junior developers, wrote an article about how to contribute to Grafana as a junior dev. As an open-source project supported by engineers around the world, Grafana strongly encourages anyone to contribute. And ICYMI, there are many opportunities to help: Testing the UI and reporting issues, finding and fixing bugs, and improving the documentation are just a few.
StackStorm is headed for the Linux Foundation! This is a big move and we're excited to share this news with our community. For several months now we've been working with the Linux Foundation, the StackStorm team, and many others inside Extreme to make this move possible. We want to thank everyone for their effort to make this move happen. StackStorm's community continues to grow and the impact the project has had continues to show, and show, and show, and show (you get the point).
Instrumenting the performance of custom code (the code you write, not the libraries you require) in web apps has been a thorn in my side for years. Yes, we have a custom instrumentation API, but raise your hand if you enjoy sprinkling your code with this? Anyone? Having a custom code instrumentation blackhole doesn't matter if your app spends almost all of its time in common libraries that Scout instruments by default (ex: ActiveRecord, Redis, View Rendering, and HTTP calls).
Here at Lumigo, we are big fans of serverless. And a big part of working with AWS Lambda involves using many other AWS services. For example, services such as SNS and SQS are often used to chain Lambda functions together. They are essential ingredients of an event-driven architecture, where systems are loosely coupled through events. However, they also pose a challenge to how we test our systems and how to get fast feedback on what’s happening in the system.
Many companies today try to feed business metrics into APM or IT monitoring systems. Splunk, Datadog and others track your business in real time, based on log or application data – something that would seem to make sense. In practice, however, it fails to produce accurate and effective monitoring or reduce time to detection of revenue-impactful issues. Why? Because monitoring machines and monitoring business KPIs are completely different tasks.
IBM Cloud Log Analysis with LogDNA enables you to quickly find the source of issues and gain deeper insight into application and cloud environment data. IBM Cloud logging begins with log aggregation from application and services within IBM Cloud. IBM partners with LogDNA to bring collection, log tailing and blazing fast log search. LogDNA supports integrations to many cloud-native runtimes and environments.
It’s no secret that machine learning (ML) has experienced tremendous growth and adoption over the last few years. And why not? This exciting technology has enabled us to utilize the power of machines for a wide variety of applications and industries. From image processing to predicting to medical diagnosis, ML has begun to reshape the way we live.
Every successful company plans for sustainability and growth. Forecasting the growth path helps companies set their short- and long-term business objectives and make important decisions to help them reach their goals. Short-term forecasts are important in quarterly and annual budget planning and for ensuring that daily business operations help achieve long-term goals.
In the beginning, there was a developer using Graphite, and he found its user interface lacking. Then he discovered the Kibana project, liked its UI, and forked it. Grafana was born in 2013. “I started Grafana to do something similar as Kibana, but focused on time series metrics. My goal was to make time series data accessible for a wider audience, to make it easier to build dashboards, to make graphs and dashboards more interactive,” says Torkel Ödegaard.
