Datadog Reviews

Datadog is expensive. 

The tool's deployment is easy. 

The solution's pricing depends on project volume. 

I rate Datadog a seven out of ten. 

We use actual user monitoring and have set up thresholds for alerts to PagerDuty, Sentry, Slack, and so on. We also have dashboards set up for tracking latency and error rates. 

As an individual contributor, I also try to set up dashboards for the individual feature projects I work on. I'd like to learn more ways to use this, though, especially when it comes to more proactive approaches to issues. A starter pack of common-use types would be nice.

The solution it has improved our organization by expanding the awareness of issues and alerts beyond SRE and really empowering software engineers at a team level to make changes to monitoring and incident responses.

There could still be more training to bring this even further. A lot of the time I get into Datadog and it's already an incident and I am not in the right mindset to learn about the product or set alerts up.

The feature I have found most valuable is when I can reuse existing monitors and alerts for new dashboards. 

It is nice that things are so integrated, and any individual thing I build out can likely be re-used across the suite.

Other features I have found useful include the stack traces, especially when it links back to something specific I can look for in the code base. I also like that you can group similar alerts together to look for trends over time instead of one in isolation and see if there have been regressions.

The biggest improvement would be around educational content and helping new users get started. I've only been using Datadog for a few months, and at first, it was frankly overwhelming in terms of both the UI and the available capabilities. The workshops today have helped with this, however, more could be done.

As a user, I have about six or more months of experience with the solution. As a company, I'm not sure.

I was not in charge of evaluating any other solutions.

We use the solution for monitoring our logs across distributed clusters. Right now, we have an Elasticsearch solution that is tied to each platform (our product is a PaaS solution). 

We are looking at moving to a single pane of glass solution, which Datadog would be good for (plus, we could wrap up other tools like Prometheus, Grafana, Pagerduty, Pingdom, and more). We want to be able to have Datadog running on one single cluster and ingesting and processing logs from all our distributed clusters.

So far, we are just in the evaluation stages so it's hard to say how it's improved out organization. However, one positive impact it had is it's been just showing us an example of how to build in observability, metrics, tracing, etc., in a better way. 

Even if we don't end up using Datadog, it revealed problems and optimizations to us that weren't obvious before. One potential reason why it may not help us is that we have strict rules around log parsing and may not be able to send it to an external organizaton for ingestion/processing.

The CPU profiler has been interesting even though it isn't our core use case. 

We are finding that Datadog has way more offerings than originally expected, so we are constantly finding new parts of it that would be convincing to use. 

The log and ingestion are very similar to our current Elasticsearch setup. We find the tracing and overall integration/ecosystem to be the most valuable part. Basically, the CPU profiler is a good example of a value add for a problem we knew we had yet was low priority and had hacky workarounds. The value proposition is in the ecosystem as a whole.

The sheer amount of products that are included can be overwhelming. 

The solution requires better overarching UI, which would make things clearer. Even though I generally dislike the AWS UI, it makes the different services very clear, and it also makes where you are at any given point clear. 

The sidebar for all the different services is a bit much. 

I also found the tagging of logging pipelines to be a bit tedious. It would be great if, once marked up, it would automatically be a first-class citizen in Datadog.

We are still in the evaluation stage and have used it less than one month.

The stability looks good so far.

It seems easier to scale and build app functionality across multiple teams rather than other solutions.

We have used Elasticsearch, Grafana, and Prometheus. We are still evaluating Datadog.

The product has provided good ROI by saving development time as well as time managing setting up ES.

It is somewhat expensive compared to open-source options.

We evaluated Elasticsearch, Grafana, and Prometheus. We are still evaluating Datadog.

We use different tools for log collection and monitoring. Using Datadog will combine different use cases into one product that will be easier to manage. 

The tools we use are open-source, so there is no commercial support. Having customer support would be ideal since we're a small team. 

Profiling would be another great feature to have. Currently, it's manual. Having Datadog would give us a standard, and we don't have to do much manual work.

It will solve a lot of our problems. We have different tools for each of them in our organization; they are open-source and therefore not very well maintained with there is no customer support. 

Having an industry-standard product such as Datadog would be ideal for us as we are short on manpower. Since this is a managed all-in-one product with readily available support, we will be able to focus on application logic rather than figuring out why a tool isn't working.

The biggest thing I liked was the combination of all the things - monitoring, log aggregation, and profiling. We have different tools for each of them in our organization and all of them are open-source. These are not very well maintained and there is no customer support. 

Having an industry-standard product is ideal for us as we are short on manpower. Profiling is another amazing feature. Currently, we rely on some open-source solutions, and it's all done locally. Having it done on Kubernetes would give us more insights and help with performance. Alerting is again a nightmare for us. Datadog solves all of these issues.

It can be overwhelming for new people as it has a lot of features. The UI could certainly be improved. Having less information with better organization could help newcomers. I haven't seen the documentation, however, a well-organized documentation would invite many varied users.

I've been using the solution for three years.

We are using Datadog for server metrics, log aggregation and searching, system monitoring, alerting the team about errors, and dashboards for our developers. It's used by the Site Reliability Engineering team and Management of all levels. 

It's assisting us in proving SOC II compliance. 

We're looking to improve our usage of Datadog's RUM and APM components to get better and more performance insights on our production environments. 

We're also looking to leverage more synthetic monitors and runbooks for anyone responding to incidents.

The ability to easily drill down into log queries quickly and efficiently has helped us to resolve several critical incidents so far this year, and we heavily rely on a series of dashboards showing us various queues and load on CPU and memory for servers. 

We also have a view of the information required when we begin the patch and/or upgrade processes. 

I've also set up several monitors to alert the Site Reliability Engineering team when various metrics show a server might be reaching capacity. We use it to send an email suggesting we increase the size of the cloud instance.

The ability to easily drill down into log queries quickly and efficiently has helped us to resolve several critical incidents. We heavily rely on dashboards that are showing us various queues and load on CPU and memory for servers. 

We also have a view of the information required when we begin the patch and/or upgrade processes. 

I've arranged several monitors to alert the Site Reliability Engineering team when various metrics show a server that might be reaching capacity. We use it to send an email suggesting we increase the size of the cloud instance.

Datadog could always lower the price! In general, more demos online and maybe more free hands-on tutorials for basic functionality would be good for less technical users. 

I would also prefer more chances to amend the contract more than twice a year. As a smaller but growing company, it can be difficult to adequately predict demand.

I've used the solution for more than three years.

We use the application for our application monitoring, data security monitoring, and log management. What we like about the application is that it helps us to track issues more proactively instead of reactively.

There are other improvements we would like to see.

1. Being able to restrict users from seeing or viewing specific dashboards once they log in

2. They can cut down the prices for Cloud SIEM. It seems very useful, however, the prices are high. Some organizations are finding it difficult to make decisions in terms of getting the tool.

We use the application for our application monitoring, data security monitoring, and log management. It helps us to track issues proactively instead of reactively.

It helps us better manage our logs.

We can effectively track down issues.

We have dashboards that give us an overview of our environment.

The tools I have found useful include the Datadog cloud security posture manager and cloud workload security.

Datadog is a great tool, and we value the services they offer. They should continue expanding and integrating with more third-party apps.

I've used the solution for three years. 

I love its stability.

It is very scalable.

Technical support has been great.

Positive

We previously used AWS.

The initial setup is not too complex.

We've seen an ROI of 50%.

It's a little pricy yet worth it.

We did not previously evaluate another solution.

We use an enterprise version of a CMS platform which is enabling businesses to transmit content to their customers. The tool is fully customizable to the end user, including out-of-the-box integrations as well as APIs for custom plugin support. 

Our systems fully manage content using AWS as the back-end cloud provider. Assets are kept in secure buckets and utilize the Kubernetes infrastructure to deliver our product to end users and internal authors. Using the CMS allows for business people to manage content without needing development efforts.

This tool is the sole purpose of my company and the solutions we provide around it. Enabling customers to manage their content in a fast, reliable, and highly user-friendly setup has been critical to our success. 

Offering our product at SaaS, PaaS, cloud, and on-prem editions has enabled us to provide a solution for all types of customers. 

The platform appeals to companies spanning many industries on a global scale. 

Being based in SUI allows us to secure both the EU and other companies more easily.

The enterprise version of a CMS platform enables businesses to transmit content to their customers. 

The tool is fully customizable to the end user, including out-of-the-box integrations as well as APIs for custom plugin support. 

The content is fully managed within our systems using AWS as the back-end cloud provider. Assets are kept in secure buckets, and we can utilize the Kubernetes infrastructure to deliver our product to end users and internal authors. 

Using the CMS allows for business people to manage content without needing development efforts. Allowing this type of setup for business users has been a key reason for our success.

There is always room for improvement when dealing with cloud-based technologies. Mainly, I would say, it's just increasing our offerings to attract various other types of industries and businesses across more fields. 

New features as requested by our existing customers will help make the product better.

The product was self-developed.

We use a SaaS deployment. 

We primarily use the solution for observability, metrics, logs, tracing, and end-to-end user flow monitoring. 

We are looking to implement this as a company-wide standard for cloud solutions.

At this time, we're currently in a POC, and we're interested in using either a Datadog agent or the OTel agent with a Datadog exporter. We have dashboards with panels that correlate metrics and allow you to link through to traces. Flame graphs to show latency across services and the various spans. 

While we are not security minded, we still require it and are interested in more. It's used for monitoring critical systems.

It has provided visibility with ease of implementation and allowed multiple teams to quickly onboard it. This provided a standard way to approach observability and visibility. 

Monitoring rules and alerting thresholds can also be set and exported to other teams for use. 

There is an issue with federated dashboards, as multiple teams running on different Datadog instances cannot use features like the service catalog or easily switch between services in a long business flow.

The K8 monitoring is extremely useful in Datadog. Preset dashboards that it provides help to speed up the work. 

The metrics summary is useful. Tracing with a span breakdown is helpful for us. We like the dashboarding with power packs and logging correlation with traces and logs. 

The Flame graph for tracing helps determine where the latency is the highest. 

Dashboards are created as a standard set and then exported into other Datadog instances for other teams. 

These dashboards would be updated regularly and pushed out to the teams. Unfortunately, there is no way to automatically push or deploy code in a quicker way. Each team I work with has its own Datadog instance.

Federated views for Datadog dashboards are critical as large companies utilize multiple instances of the product and cannot link the metrics or correlate the metrics together. This stunts the usage of Datadog. Additionally, using an OTel agent would be more acceptable and allow for easier adoption of Datadog across the hundreds of teams here.

I've used the solution for four months.