Operations | Monitoring | ITSM | DevOps | Cloud

Stackery Welcomes Tim Wagner, Inventor of AWS Lambda, to Board of Directors

In new and quickly-expanding fields like serverless, long-standing experts are few and far between. I am excited to welcome Tim Wagner, the original leader of the serverless movement, to the Stackery Board of Directors. Tim spent six years at Amazon Web Services as the General Manager of AWS Lambda, where he oversaw the team that built the success of serverless as a platform. In many ways, we have them to thank for creating the environment that supports Stackery and the serverless ecosystem.

Monitor Vertica analytics platform with Datadog

Vertica is a platform that uses machine learning capabilities to help you analyze large amounts of data. Vertica provides high availability and parallel processing by replicating data onto multiple nodes in a cluster, and uses a column-based data store for efficient querying. You can deploy Vertica in the cloud, on premise, or as a hybrid of the two.

New Resources for Contributors to the Grafana Project

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 joins the Linux Foundation

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).

Introducing AutoInstruments: zero-effort performance monitoring of custom Ruby code

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).

Introducing the lumigo-cli

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.

Don't Treat Your Business Metrics Like Other Metrics

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 Log Analysis with LogDNA

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.

The Top 3 Use Cases for Machine Learning in Analytics and Monitoring

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.

Growth Forecasting Use Cases for Anodot's Autonomous Forecast Solution

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.