Operations | Monitoring | ITSM | DevOps | Cloud

5G is in the process of transforming communications technology, enabling never-before-seen data transfer speeds and high-performance remote computing capabilities.

Connected devices will obviously have a firm hold of various industries in the present. Since the pandemic Covid 19, has affected every aspect of our life, the evolution of innovations in IoT has been impacted a lot in the daily life of people amid the crisis. The connection between the world is being made easily possible with increased use cases with the IoT devices, which connects appliances and initiates the exchange of information.

When it comes to conversations around application architecture or working with integrations between applications, you’ve likely heard a couple terms pop up a few times: microservice and APIs. You might also have run across the common misconception that microservices are just a way to implement APIs so they can communicate with each other. As you’ll see in this article, there are alternative ways to architect our microservice applications.

Get started with Gremlin's Chaos Engineering tools to safely, securely, and simply inject failure into your systems to find weaknesses before they cause customer-facing issues. API gateways are a critical component of distributed systems and cloud-native deployments. They perform many important functions including request routing, caching, user authentication, rate limiting, and metrics collection. However, this means that any failures in your API gateway can put your entire deployment at risk.

With our ability to ingest GCP logs and metrics into Splunk and Splunk Infrastructure Monitoring, there’s never been a better time to start driving value out of your GCP data. We’ve already started to explore this with the great blog from Matt here: Getting to Know Google Cloud Audit Logs. Expanding on this, there’s now a pre-built set of dashboards available in a Splunkbase App: GCP Application Template for Splunk!

We're excited to announce that autoscaling is now available on Elastic Cloud. In our initial release, autoscaling monitors the storage utilization of your Elasticsearch data nodes and the available memory capacity for your machine learning jobs.

Logz.io has always prided itself as a company pushing the use of open source tech. As we have moved to expand our reach with metrics and traces over the past year and a half, we have doubled down on our own contributions to the community. With (distributed) traces in particular, we have been able to forge ahead. Our relationship with the teams at Jaeger and OpenTelemetry have really blossomed (and we are kind of proud to have supported the latter in the run-up to the OpenTelemetry v1.0 release).