Operations | Monitoring | ITSM | DevOps | Cloud


The Challenges of Partition Rebalancing in Kafka Brokers and Effective Monitoring Strategies

Apache Kafka has become an essential component in data streaming and processing architectures due to its high throughput and scalability. However, as organizations scale up their Kafka usage, they often encounter challenges such as partition rebalancing across different brokers. This imbalance can lead to significant issues, including overloaded partitions that jam traffic, affecting performance and reliability.

Overcoming Azure Service Bus Monitoring Challenges

Monitoring Azure Service Bus (SB) comes with its own set of challenges, primarily due to the distributed nature of the service and the complexities involved in message processing and delivery. Some of the most common challenges associated with monitoring Azure SB include: Message Flow Monitoring: Tracking the flow of messages through various queues or topics, including understanding where bottlenecks might occur or where messages might be delayed.

Strategies for Ensuring Compliance in Financial Messaging

In the ever-evolving landscape of financial services, institutions are under constant pressure to ensure their messaging infrastructures comply with a myriad of global regulatory requirements. Compliance with regulations such as the General Data Protection Regulation (GDPR), the Payment Services Directive 2 (PSD2), and other localized financial regulations is not just a legal necessity but a cornerstone for maintaining trust and integrity in the financial sector.

Optimizing Performance and Reliability in Messaging Systems

In today’s digital landscape, the performance and reliability of messaging systems are paramount for business operations. Systems like IBM MQ play a crucial role in ensuring seamless communication between different parts of an application, impacting everything from transaction processing to customer experiences. To optimize these systems, it’s essential to focus on robust monitoring, efficient troubleshooting, and effective tuning techniques.

Lessons Learned from Managing Kafka Costs

You probably have seen ads where someone claims that their app can save you money by finding subscriptions you forgot about. I have a hard time imaging someone with $100s of dollars of expenses they forgot about, but I have had the occasional one that was missed. The problem is that people are inefficient when it comes to managing “stuff”. That is why there are so many places to store “stuff”.

How a Modern Integration MESH Changes our Roles and Responsibilities

There was a time not too long ago, before the cloud was a part of every enterprise technology conversation, when integration work was considered the purview of a specific architecture and engineering group. If messages failed to send, or services failed to respond, application stakeholders would create a trouble ticket for the integration team to address. In some ways, this separation of labor was effective enough at the time.

Delivering Distributed Transaction Tracing Across Integration MESH

Distributed transaction tracing (DTT) is a way of following the progress of message requests as they permeate through distributed cloud environments. Tracing the transactions as they make their way through many different layers of the application stack, such as from Kafka to ActiveMQ to MQ or any similar platform, is achieved by tagging the message request with a unique identifier that allows it to be followed.

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meshIQ - Seeking Partners to Deliver Observability Across Integration MESH

In today's rapidly evolving technological and business landscapes, staying competitive requires more than just a great product or service. It demands a technological edge that can drive efficiency, innovation, and overall growth. This is where partnering comes into play - it's like turbocharging your business engine. Today, meshIQ is looking to turbocharge our sales teams, processes, and reach by adding power via partnerships.

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3 Reasons to Prioritize Observability as part of Application Integration Strategy

Most companies in today's business landscape that deal with large amounts of data want to integrate their applications so that they can pass data between them seamlessly and easily. Being able to ensure that you can see exactly what is happening at every stage of the process is key, and this is where approaching the process with observability in mind can make a real difference. Deciding at the outset that observability is something that you want to be baked into the process means that you can plan and execute with that in mind.

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Improve MTBF and MTTR for your Application Platforms by using MESH Observability

When businesses look at how best to understand the performance levels of their platforms, some of the best incident management metrics to look at are Mean Time Between Failures (MTBF) and Mean Time ToResolution(MTTR). These two measurements will give an excellent indication of the health and speed of the system, as well as the ability of the platform to take care of any anomalies that have been detected or to flag them up for others to take action to resolve them.