Operations | Monitoring | ITSM | DevOps | Cloud

Programming is often thought of purely as a problem-solving activity. This may be true for the lone coder in their garage, but in the multi-person environment of an Agile team, such problem solving must be collaborative. In this article, we’ll look at the role of communication in software development, particularly in an Agile framework. Covid-19 has forced an unprecedented shift to remote working so we’ll finish up with a discussion of how Agile can be implemented in a remote setting.

Consider for a moment that you are building a webpage that displays data stored in Elasticsearch. You have so much information in your index that your API Gateway cannot handle it all at once. What you’ll need to do is paginate your results so that the client can have a predictable amount of data returned each time. Before paginating your results with your client, you will need to know how to paginate data in your backend storage.

Hybrid cloud architectures provide the flexibility to utilize both public and cloud environments in the same infrastructure. This enables scalability and power that is easy and cost-effective to leverage. However, an ecosystem containing components with dependencies layered across multiple clouds has its own unique challenges. Adopting a hybrid monitoring strategy doesn’t mean you need to start from scratch, but it does require a shift in focus and some additional considerations.

Metrics measuring user engagement on your website are crucial for observability in marketing. Metrics will help marketing departments understand which of your web pages do not provide value for your business. Once known, developers can look at the web page’s technical metrics and determine if updates are required. Typically user engagement statistics, like the average time required to load your page, are stored separately from technical site logs.

For the seasoned user, PromQL confers the ability to analyze metrics and achieve high levels of observability. Unfortunately, PromQL has a reputation among novices for being a tough nut to crack. Fear not! This PromQL tutorial will show you five paths to Prometheus godhood. Using these tricks will allow you to use Prometheus with the throttle wide open.

The widespread adoption of Agile methodologies in recent years has allowed organizations to significantly increase their ability to push out more high quality software. Previous development practices revolved heavily around centralized applications and infrequent updates that were shipped maybe once a quarter or even once a year.

Mean time to repair (MTTR) is an essential metric that represents the average time it takes to repair and restore a component or system to functionality. It is a primary measurement of the maintainability of an organization’s systems, equipment, applications and infrastructure, as well as its efficiency in fixing that equipment when an IT incident occurs. Key challenges with MTTR arise from just trying to figure out that there is actually a problem.

The modern technology landscape is ever-changing, with an increasing focus on methodologies and practices. Recently we’re seeing a clash between two of the newer and most popular players: DevOps vs DevSecOps. With new methodologies come new mindsets, approaches, and a change in how organizations run. What’s key for you to know, however, is, are they different? If so, how are they different? And, perhaps most importantly, what does this mean for you and your development team?

11 Tips for Avoiding Cloud Vendor Lock-In Cloud vendor lock-in. In cloud computing, software or computing infrastructure is commonly outsourced to cloud vendors. When the cost and effort of switching to a new vendor is too high, you can become “locked in” to a single cloud vendor. Once a vendor’s software is incorporated into your business, it’s easy to become dependent upon that software and the knowledge needed to operate it.

Metricbeat, an Elastic Beat based on the libbeat framework from Elastic, is a lightweight shipper that you can install on your servers to periodically collect metrics from the operating system and from services running on the server. Everything from CPU to memory, Redis to NGINX, etc… Metricbeat takes the metrics and statistics that it collects and ships them to the output that you specify, such as Elasticsearch or Logstash.