For many years, ELMAH was the go-to logging utility for ASP.NET. It caught exceptions that came up through the IIS response pipeline and logged them along with contextual information. It also put a subpage on your site that you could visit to view logged exceptions. It was a great tool for catching, logging, and viewing unhandled exceptions for monolithic ASP.NET applications. But now that we’ve moved to distributed application architectures, we need something more.

Investing in a log analysis tool provides many benefits: it saves time needed to detect and troubleshoot a problem, reduces churn by providing a better user experience, and improves system security. There is a wide scope of use cases for log analysis - from tackling security and performance issues head-on to enhancing the quality of your services. What are some of the most common use cases for log file analysis?

LogDNA today announced a new offering that enables developers to troubleshoot coding bugs and quickly fix development errors in applications, potentially saving businesses millions of dollars in development hours, downtime and associated revenue loss. IBM Log Analysis with LogDNA integrates LogDNA services to allow developers to aggregate all their log data across applications in the IBM Cloud.

With an Access logs viewer, you can search and filter for specific messages, analyze them and improve your website performance and users experience.

Elastic Stack 6.5 is out! Every new version of the Elastic Stack is packed with new features and updates, and as always, I’m happy to dive a bit deeper into the new release to provide our readers with a wrap up of what’s new. Interestingly enough, and as reflected in the announcements surrounding this release, this release is all about Kibana. That’s not to say the other components in the stack were left out – to the contrary, and I will cover them all, don’t you worry.

Today at Amazon Web Services (AWS) re:Invent we announced some new applications and integrations with popular AWS services, including the newly-released AWS Security Hub, AWS WAF and AWS Aurora for MySQL and PostgresSQL.

Website performance is a burning issue that matters to any IT professional who is responsible for the company’s website. Access logs performance analysis is used for analyzing all access logs for website performance: slow page load time, most frequent web pages and their errors, large web pages issues and more.

In the digital era, we need to track and record all of our data at all times. From a user logging into the dashboard to database queries, JavaScript errors, and website traffic, everything that matters is recorded in a log. You name it, and with due probability, you already have time-stamped documentation of all the events saved somewhere in the form of a log.

Every year, we take time out of our everyday activities to join thousands of techies just like us for the biggest event of the season–AWS re:Invent. For one week at the end of November, industry leaders gather in Las Vegas to learn about new technologies from AWS as well as other partners in the cloud, DevOps, and IT spaces. The new technology, innovative ideas, and smart, ambitious people we have met over the past few years have been priceless for all of us at Logz.io.

One of the major developments in software design and delivery over the last few years has been a movement away from monolith applications towards microservices. One of the sticking points I’ve seen on numerous microservice applications is logging. There are some unique challenges with microservice logging that need to be addressed. In this article, we’ll look at how we can make logging in a microservice as painless as in a monolith.

With so many choices available to us today, choosing log management software that’s just right for us has never been simpler. That is, if you know exactly what it is you are looking for. But for many users, the sheer amount of computer programs that perform the same tasks, and seem so similar(sometimes almost identical) to each other, can quickly become off-putting and confusing.

In the world of agile there’s a demand to solve grey areas throughout the design process at lightning speed. Prototypes help the scrum team test ideas and refine them. Without prototypes, we can’t test ideas until the feature or product has been built which can be a recipe for disaster. It’s like running a marathon without training.

Organizations that handle logging at scale eventually run into the same problem: too many events are being generated, and logging components can’t keep up. Even with persistent queues and other mitigating features enabled, there’s simply not enough of a buffer between log generators and log ingesters to handle the volume of log lines coming in.

Application Performance Monitoring, aka APM, is one of the most common methods used by engineers today to measure the availability, response times and behavior of applications and services. There are a variety of APM solutions in the market but if you’re familiar with the ELK Stack or are a Logz.io user, this article describes using a relatively new open source-based solution — Elastic APM.

Logging is an important topic in software development, especially if you need to analyze bugs and other unexpected events in your production environment. Implementing your logging often seems easy. But as you probably experienced yourself, logging is far more complex than it might seem. That’s why you can find lots of articles about it here on the blog.

Ever since humankind developed the ability to write, much of our progress has been made thanks to recording and using data. In ages long past, notes were made on the production and gathering of resources, the exact number of available soldiers and other important personnel, and were compiled and stored by hand. Because of this documentation method, important information was also prone to being misplaced, lost, or even mishandled.

I hosted a webinar where I covered why logging is important, how to choose a logging provider. And then shared our experience of setting up logging on Kubernetes containers, the Kubernetes logging framework and the logging best practices we’ve implemented internally and supported our customers who run Kubernetes in production.

Last month, we announced Logz.io Security Analytics — a security app built on top of the ELK Stack, offering out-of-the-box security features such as threat intelligence, correlation, and premade integrations and dashboards. In this article, I’d like to show an example of using both the ELK Stack and Logz.io Security Analytics to secure an AWS environment.

We recently had a presentation at Activate 2018 about entity extraction in the context of a product search. For example: how to tell, when the user typed in Activate 2018, that the intent was to run conference:Activate AND date:201

Servers take a lot of requests daily, we know that…We also know that the server responds instantly. But who makes the request? What do they want, and what exactly are they looking for? Where do these visitors come from? How often they are making a request: once a month, once a day, almost every minute? Well, answers to these, and potentially a lot more questions, can be found in a single place - the server log file.

We’re excited to announce that LogDNA’s built-in log parser offers custom parsing, now available in beta. This means you can now use our step-by-step wizard to wrangle non-standard log formats and run custom transformations on your logs, allowing you to easily search and graph log lines that were previously off limits. The best part is, it’s a simple three step process: search, extract, validate… done!

One of the most important aspects of developing an efficient system is to have clean, helpful logs that will help you understand what errors are being triggered, and what information is being processed. When you are first creating an application, you might not know what logging framework will be most suitable for your future needs, or you could simply want your system to remain agnostic regarding the logging implementation to be used.

One of the greatest threats to a log management solution is load. As log volume increases, the ability for a solution to process each event decreases. Given enough load, this will result in dropped messages and data loss.

We are very excited to announce a new capability for our Amazon S3 sources. Until recently, the only method Sumo Logic used for discovering new data in an S3 bucket was periodic polling. However, with our new notification-based approach, users can now configure S3 sources such that Sumo Logic is notified immediately (via AWS SNS) whenever a new item is added to an S3 bucket, eliminating the need to wait for new objects to be discovered via periodic polling.

We’re excited to announce the general availability of our new On-Prem, Self-Hosted, and Multi-Cloud logging platforms. Our customers will have the capability to log data in their infrastructure of choice. Whether across multiple public/private clouds or within a customer’s own data center, logs can be viewed through a unified interface while addressing any data locality and performance requirements.

Recently, we held a webinar where Chris Nguyen, our CEO and Co-Founder and Norman Hsieh, our Head of Business Development talked about the ever increasing production of data, the shift from monitoring to observability, and the evolution of production infrastructure into multi-cloud. LogDNA is uniquely positioned to have enabled thousands of customers to gain deep insights into their evolving DevOps infrastructure.

As any business running microservices, containerized applications, networking devices, or multiple servers knows, it’s important to get a centralized log management system that fits your company’s unique needs. The best log management solution should empower your business to gain insights, resolve production issues quickly, streamline your DevOps and IT teams, and allow you to work more efficiently.

In organizations which uses a Windows server environment, the vast majority of authentication and access control processes are managed within Active Directory. As a central and critical component for managing organizational IT resources, Active Directory logs contain valuable information which must be closely monitored and analyzed.

What is log monitoring and log analysis? Both are crucial parts of log management and related in many capacities, but by definition, the two actually have different core meanings.

Addressing compliance requirements for monitoring and logging can be a challenge for any organization no matter how experienced or skilled the people responsible are. Compliance requirements are often not well understood by technical teams and there is not much instruction on how to comply with a compliance program. In this article, we’ll discuss what some of these new compliance programs mean, why they are important, and how you can comply with your logging and monitoring system.