There are numerous reasons to consider a log and data event management tool. To start, here are customer stories we have consolidated to share the benefits of implementing a logging solution into your team’s workflow! Let’s dive into what customers have said about why they chose DataSet, but more importantly how they are using log management to improve their software development process and productivity.

1. Fast Data Ingestion - Petabytes to Scale

One of DataSet’s strongest assets is providing blazing speeds of data ingestion. It is clear that most teams evaluating logging and observability tools are looking for the easiest and most effective way to scale and search through high volume data. When Zalando migrated from a monolithic code base to a microservices architecture, their teams prioritized being able to access all data within their new complex architecture. Instead of trying to find which hosts were running on which services and manually pulling logs from each host, their DevOps teams simplified by ingesting all services in DataSet for instant searches.

An online retail company reduced log search time by 98% from hours down to seconds

While some customers were beginning their journey in the logging space, others were opting for a new solution opposed to their current legacy competitor tools. A leading talent management software company found a competitor tools’ ingestion performance too slow and noticed their service slowing down as data volume ramped up. On the other hand, a popular online dating company decided to opt-in for a buy solution with DataSet versus their ELK based in-house solution.

As a result, both of their engineering teams found a similar reduction in log search time to that of Zalando’s and did not have to worry about storage capacity.

2. Simplify the Journey from Monoliths to Microservices

There are many benefits to moving your architecture to microservices, but there are caveats to consider. For example, engineering teams at Wistia needed a single solution to provide real time visibility into their entire cloud environment. They used DataSet to gain insight into their containerized applications which were being deployed on Amazon EKS. Knowing that DataSet effortlessly unifies logs spread across all microservices, infrastructure, and applications they’re running on, the team was able to gain insight with Kubernetes.

Likewise, the previously mentioned talent management company was able to equip their Cloud Operations team with similar visibility across all applications, cloud stacks, and containers on Amazon ECS. They were able to have all the access they needed to web server logs and applications from DataSet.

A leading talent management software company enhanced its migration to microservices by being able to detect performance issues in seconds - which took competitors 10 minutes

When moving from traditional data centers to Kubernetes, Copart decided to make the jump to log management. They quickly scaled all their logs in order to increase response times to query, thus improving scalability and performance in operations.

Lastly, Asana, found their applications lacked visibility and transitioned from running scripts to download logs from their S3 buckets to running Kubernetes frameworks to connect their logs for easy central visibility across the entire tech stack.

As you can see, it is generally easy to deploy an agent and start ingesting logs with cloud-native tools like DataSet.

3. Total Cost Reduction

Developer team leaders can attest to a significant decrease in total cost of ownership when looking at the big picture effects of log management. In fact, noted by Copart’s CISO, DevOps and Security teams downsized from two log management solutions to one, with DataSet. They were able to respond to incidents quicker due to aggregated data across servers, routers, infrastructures, and ensure application uptime.

Copart's CISO recognized a drop in total cost for DevOps teams due to more integrated system and network logs and increased latency

Another benefit is that DataSet does not charge by the number of users. Some teams feel like they can scale infinitely in relation to product adoption and not worry about uncertain overages.

4. Make Data Accessible to All

No need to worry about the gatekeepers of information with a log management tool as accessible as DataSet. It’s no surprise that making data sets accessible to an entire team benefits everyone. When it came down to sharing a data lake, Zalando enabled hundreds of their small autonomous teams to take ownership of one or more platforms. By having a centralized variety of logs available to search at scale for everyone, DataSet was adopted by 200 teams made up of over 1,000 engineers.

Engineer, Security, DevOps, Support teams all make use of log management resources

Who else can take advantage of logs besides DevOps and security teams? Wistia, chose to give access to log management for their Technical Support team and found success in usability and self-serve purposes. Its tech support team used DataSet to track the root cause of customer issues using the search function to pinpoint requests within the logs. By analyzing customer encounters, they were able to identify and best solve common problems.

5. Custom Parsing - See What Matters

Parsing common log types makes it easy to ingest data so that they’re easy to search and analyze. Customers previously mentioned, such as Zalando and Wistia, found usefulness in custom parsing, ease in implementing on instances and out-of-the-box agents, as well as flexibility with formatting rules.

An online dating company's operations team saves thousands of engineer hours with custom parsers, configuring to extract fields from custom log formats

An online dating company found its match with DataSet’s custom parsing ability. Within their journey, they were able to deploy in production environments, set up the parser, and track down issues in only minutes. Traditionally, it would take hours to query data and pinpoint important levels of information, but with parsing it only takes minutes to track down relevant issues.

DataSet provides Built-In Parsers for common log formats and also allows for custom builds as well.

6. Easy Integrations

It's possible to aggregate logs from thousands of services with no management overhead. You can use the DataSet API to send and retrieve log data, archive events, and manage configuration files, users, and groups.

Asana onboarded logs within their Kubernetes framework, making it easy to find logs across different clusters

Going from one application to another is simple. As shown by Asana, their teams were able to find the root cause of incidents and correlations at lightning speed with Kubernetes.

Teams can experience the benefits of DataSet on all cloud platforms – from Amazon ECS, Google, to Microsoft Azure and more.

7. Identify Errors with Alerts

DataSet’s many integrations across platforms like email, Slack, PagerDuty, OpsGenie allow for instant alerting to flag important incidents. Many customers found that log management helped their teams identify errors and mitigate the incidents as a response. One company found that increased troubleshooting led to debugging productivity across their engineering team and as a result they were able to resolve customer-facing issues quicker - cutting resolution time by 80 percent.

It’s easier and faster to diagnose bugs that frustrate customers - Infrastructure Engineering Lead, Wistia

While some competitor tools do not provide easy access to web server and application logs, DataSet does so you can spend less time searching through them. What do you do when there is an outage? On-call engineers can quickly find logs that correlate and decide to scale up or down or deploy fixes. If you are dealing with Kubernetes, instead of figuring out which pod has errors and trying to find error logs from there, all the logs are shown in DataSet.

DataSet Has All The Features

Our platform is built for experiencing the speed, scale, and efficiency of enterprise data. Learn more about our features, such as schema-less ingestions, parsing and preprocessing data, live streaming data, parallel query engine, secure storage, and cloud architecture, to make an informed decision when evaluating your next log monitoring solution.

These features allow you to do all sorts of things, including and not limited to:

  • Streaming data from a broad range of log shippers, queues, agents, distributed stream processors, and APIs in milliseconds
  • Acquiring visibility on structured and unstructured data upon ingestion
  • Viewing live dashboards materialized by repeat queries, which alerts trigger at machine speed and automate tasks execute in real-time
  • Searching encrypted data instantly in a security-first platform
  • Experiencing cloud scale

Get Started Now

Teams choose DataSet to elastically scale to petabytes of data while delivering real-time performance at a fraction of the cost. We invite you to try a fully-functional DataSet for 30 days at no cost.

Request a demo - We'll show you how DataSet provides unparalleled cost advantages for your specific use case.