With Solr 9 the Autoscaling Framework was removed – for being too complex and not terribly reliable – and instead we have Replica Placement Plugins. Unlike Autoscaling, replica placement only happens when you create a collection or add a new replica. Hence the name: it’s about where to place these new replicas. In this article, we’ll look at the available replica placement plugins, what you can use them for and how to use them.

When it comes to centralizing logs to Elasticsearch, the first log shipper that comes to mind is Logstash. People hear about it even if it’s not clear what it does: – Bob: I’m looking to aggregate logs – Alice: you mean… like… Logstash? When you get into it, you realize centralizing logs often implies a bunch of things, and Logstash isn’t the only log shipper that fits the bill.

Monitoring the performance of an application is not a strange concept to most developers. At one point or another, we’ve all had to do some performance debugging of our own. Usually, it happens when there’s a big issue affecting the user’s experience or cost implications. Only then do we make time to look at how the app performs in different scenarios.

Table of Contents When an application written for the Java Virtual Machine is running, it constantly creates new objects and puts them on the heap. Well, at least in the vast majority of the cases. Such objects can have a longer or shorter life, but at some point, they stopped being referenced from the code. Unlike languages like C/C++, we don’t have exact control over when the memory will be freed – freeing the memory is the garbage collector’s job.

Table of Contents Uptime is the metric that measures perhaps the most critical aspect of your business, its availability. If you think about it, having a website that does many really cool things, paying tons of money on ads to bring people to it, and even spending all those hours on making your website look great won’t amount to anything if it doesn’t work.

As your business grows, so will the number of components in your infrastructure, making manual monitoring impossible without the proper tools. Be it performance metrics, availability status, or application component logs, you need a tool that provides end-to-end visibility into the health of your infrastructure. To help you get started, we’ll compare some of the best infrastructure monitoring tools and software, both open source and paid, available today.

Table of Contents Setting up and administering multiple servers for business and application purposes has become easier thanks to advancements in cloud technology. Today, enterprises are choosing to operate large numbers of servers both in the cloud and in their data centers to meet the ever-increasing demand. As a result of these changes, monitoring technologies have become crucial. In this post, we’ll explore the best server monitoring tools and software currently on the market.

PostgreSQL is an open-source relational database that is highly flexible and reliable and offers a varied set of features. Even though it is a complex database, it provides great integrity and performance. Also, you can deploy it on multiple platforms, including a light version for websites and smartphones. Because you can deploy Postgres in different ways, it comes out of the box with only some basic performance tuning based on the environment you’re deploying on.

Ubuntu provides extensive logging capabilities, so most of the activities happening in the system are tracked via logs. Ubuntu logs are valuable sources of information about the state of your Ubuntu operating system and the applications deployed on it. The majority of the logs are in plain text ASCII format and easily readable. This makes them a great tool to use for troubleshooting and identifying the root causes associated with system failures or application errors.

Monitoring distributed systems like MongoDB is very important to ensure optimal performance and constant health. But even the best monitoring tool will not be efficient without fully understanding the metrics it gathers and presents, what they represent, how to interpret them, and what they affect. That’s why it is crucial not only to collect the metrics but also to understand them.