Operations | Monitoring | ITSM | DevOps | Cloud

Effectively, a customer portal is an online platform, usually a website or an application that allows your customers to access your services through the internet. With the help of a customer portal, they may be able to log into their account, see relevant information such policies and invoices, review past deliveries and orders, and adjust options to make your service suit their needs better.

Distributed tracing is becoming a critical component of any application's performance monitoring stack. However, setting it up in-house is an arduous task, and that's why many companies prefer outside tools. Jaeger and Zipkin are two popular open-source projects used for end-to-end distributed tracing. Let us explore their key differences in this article.

Microservices architectures have revolutionized software development, enabling scalability and flexibility. However, they also introduce complexities in system monitoring and troubleshooting. Effective logging is crucial for maintaining visibility and diagnosing issues in these distributed environments. This comprehensive guide explores best practices for microservices logging, helping you navigate the challenges and implement robust logging strategies.

Elasticsearch is primarily a search engine optimized for fast, complex search queries, especially text searches, and is often used for log and event data analysis. MongoDB, on the other hand, is a general-purpose, document-oriented database that excels in storing and retrieving structured and semi-structured data. It is commonly used for mobile, social, and IoT applications. While Elasticsearch provides superior search capabilities, MongoDB offers more robust data processing and storage features.

SaaS services are one of the biggest drivers of OpEx (operating expenses) for modern businesses. With Gartner projecting $247.2 billion in global SaaS spending this year, it’s no wonder SaaS budgets are a big deal in the world of finance and IT. Efficient SaaS utilization can significantly affect both the bottom line and employee productivity.

The IT job market has become a hot topic of conversation. With technology evolving at lightning speed and the job market shifting in response, it's more important than ever to understand the current landscape. Is the IT job market strong, or is it on the verge of a crisis?

Data aggregation includes systematically collecting, transforming, and summarizing raw data from multiple sources. A unified, consistent view helps IT teams analyze vast amounts of information, uncover patterns, and derive actionable insights for informed decision-making. In our case, it’s all about enhancing incident management.

If you’ve ever worked with Apache Kafka, you know that it’s a powerful tool, but it can also be a bit finicky. Things can go wrong, and when they do, it’s important to know how to troubleshoot and resolve those issues quickly. Over the years, I’ve encountered my fair share of Kafka errors—some that had me scratching my head for days and others that were relatively straightforward once I knew what to look for.

In a previous post, we described a CSTR and a PID controller. This post will cover the code and architecture of the digital twin from this project repo. The project leverages Kafka for data streaming, Faust for data processing, InfluxDB for storing the time series data, and Telegraf for writing data from the topic to InfluxDB. We’ll also cover the advantages and disadvantages of this stack.

To say that site uptime vendors deliver notifications is about as insightful as saying that cars have steering wheels, planes have wings, or TikTok videos have cringe. It’s a given. But this doesn’t mean that all vendors use the same notification playbook. Some vendors offer basic (read: superficial) notification features, while others offer advanced notification features.