Operations | Monitoring | ITSM | DevOps | Cloud

Over the past five years, enterprise networking has undergone a significant transformation driven by advancements in technology, the rise of cloud and SaaS applications, the decentralization of the workforce, and the need for agility, scalability, and cost mitigation. These factors have led organizations to shift from on-premise network management systems (NMS) to cloud-managed networking platforms and to adopt technologies like Software-Defined Wide Area Networking (SD-WAN).

While Artificial intelligence (AI) has invaded many industries, the IT industry is reaping the benefits of AI in software engineering practices. The traditional method of relying solely on human coders throughout the entire development lifecycle is gradually becoming obsolete. Instead, AI-augmented software engineering has come into the arena to make the software engineering process faster, easier, and more reliable.

People seem to struggle with the idea that there are no repeat incidents. It is very easy and natural to see two distinct outages, with nearly identical failure modes, impacting the same components, and with no significant action items as repeat incidents. However, when we look at the responses and their variations, we can find key distinctions that shows the incidents as related, but not identical.

InfluxDB Cloud 3.0 is a versatile time series database built on top of the Apache ecosystem. You can query InfluxDB Cloud with the Apache Arrow Flight SQL interface, which provides SQL support for working with time series data. In this tutorial, we will walk through the process of querying InfluxDB Cloud with Flight SQL, using C++. The C++ Flight SQL Client is part of Apache Arrow Flight, a framework for building high-performance data services.

In my previous articles, I discussed how to design considerations for observability solutions and how observability can augment your security implementation. In this article, I will discuss how an observability solution can provide valuable insights into your business operations through the collected data from various systems, applications, and services.

You may be thinking of investing in multiple cloud vendors to increase redundancy and deal with the complexity of your enterprise requirements. You are not alone. Many enterprises are moving in this direction to take advantage of the options offered by competing cloud vendors. Adopting one major cloud vendor is a complex project that can consume a company for months if not years.

Delivering seamless digital experiences is a top priority for every business today. However, the IT infrastructures that fuel these experiences are getting increasingly complex. The rapid adoption of technologies like containerization, microservices, and cloud and serverless computing, along with traditional infrastructure, is creating increasingly hybrid and distributed IT ecosystems, making it a challenge for organizations to manage them effectively.

We’re excited to introduce a dedicated Grafana Cloud integration for Apache CouchDB, a NoSQL document database that stores data in a JSON-based document format. Known for its scalability, availability, and easy replication of data across multiple servers, Apache CouchDB comes with a whole host of features designed to make it easy to run resilient distributed systems, with built-in bi-direcitonal replication allowing for simple replication across multiple servers and data centers.

As your Kubernetes infrastructure — and your business — grows, so too does the headache of managing your stack. And since controlling costs is crucial for your organization’s well-being, you need visibility into your complex system to ensure you’re spending your money wisely. That’s why we’re excited to introduce Kubernetes cost monitoring as a new feature in Grafana Cloud.