Operations | Monitoring | ITSM | DevOps | Cloud

Metrics and Insight have been the obsession of every sector for decades now. Using data to drive growth has been a staple of boardroom meetings the world over. The promise of a data-driven approach has captured our imaginations. What’s also a subject of these meetings, however, is why investment in data analysis hasn’t yielded results. Directors give the go ahead to sink thousands of dollars into observability and analytics solutions, with no returns.

Welcome to the second part of our three-part blog series on leveraging analytics to deliver an exceptional end-user experience. In the last part, we discussed two key points: how to gauge the effectiveness of your support forms using analytics, and how to pick the right metrics that focus on customer satisfaction. In this part, we’ll discuss the next two ways analytics can help you deliver an exceptional end-user experience.

During the Data World event, Erwin Halmans, Project Manager of Data-Driven Network Operations & Assurance at T-Mobile Netherlands, Shounit Lax-Swisa, CEO of Company Booster, and Anodot Chief Data Scientist and Co-Founder Ira Cohen got together to discuss the future of network monitoring.

During Anodot’s week-long Data World event, I hosted a panel with tech leaders Amiram.

We’d like to let you know that InfluxDB Cloud is now on AWS US East, also called us-east-1, based in northern Virginia. This is our third AWS region, after initially launching InfluxDB Cloud in AWS Oregon and later AWS Frankfurt. This brings InfluxDB Cloud’s effortless scaling, flexible usage-based pricing, AWS marketplace integration, and a broad range of AWS connectivity points to customers that want to manage their time series data in the eastern United States.

Have you ever had trouble working with Elasticsearch clusters? You’re not alone. In this post, I will discuss a problem I’ve encountered working with large Elasticsearch clusters and how I solved it. I will share a lot of knowhow on major technical Elasticsearch concepts, some diagrams for illustration, and of course a cool solution! In particular, I will go into Elasticsearch nodes, indices, and shards.

Let’s start off with some good news: since 7.9.0, your Elastic Workplace Search deployment has been collecting and logging product usage data for you and your team. Usage data like, what your users are searching for, what links they're actually clicking on, and which searches are falling short. And better yet, in a future release we’ll be putting a prebuilt Workplace Search analytics dashboard at your fingertips in Kibana, one of the most powerful visualization tools available.

We're excited to announce that indices created in Elasticsearch 7.10 will be smaller. Bigger isn't always better, and our internal benchmarks reported space reductions up to 10%. This may not seem like much for small use cases, but it's huge for teams handling (and paying for cloud storage of) petabytes of data.