Opiniones de Datadog

El envio en tiempo real de las operaciones y caidas de los servidores y bases de datos, lo que me permite una mejor toma de desiciones

La falta de un panel ejecutivo de respuesta aleatoria, me impide una mas rapida toma de desiciones

It's got everything that's needed for infrastructure and application monitoring and alerting. It also fits extremely well into our Infrastructure-as-Code paradigm where everything we set up is kept in a git repository as a Terraform project. DataDog is what we recommend and implement for our clients, and provides more useful features than Sensu.

Metrics and monitors don't render correctly on mobile phones. It's totally unusable in portrait mode, and barely usable in landscape mode.

The software can scale with the business needs. You can start with basic features or leverage many as you like (for $$) to gain deeper insights. Engineers once onboarded use it heavily to spot issues or troubleshoot more obscure bugs both in production and development.

You often need to review usage and costs. Misconfigurations, migration projects (where legacy + new infrastructures are required), integrations which may cause double reporting need to be observed to prevent run-away spend.

Datadog is a SaaS monitoring solution, that could be used to monitor different aspects of you IT infrastructure. You can find pre-configured solutions in API marketplace, which probably cover all your needs after some fine tuning, otherwise you can build your own solution. Good and responsing customer support. Stable agents

Very poor set of solutions for Microsoft Azure monitoring
Very hard for new users, documentation is not very straightforward, so you`ll need to spend a lit of time communicationg with support

Service Map, Session Replay, Custom metrics and monitors

We had a sticker shock after onboarding, as the was the hosts were counted for certain infrastructure was not clear from the documentation.

I need not have multiple monitoring solutions for different Applications. So, creating combined Dashboards/Monitors/Alerts is very convenient.

Pricing is a little on the high end, but it's definitely worth it .

Some of the pros of Datadog are:1. The APM feature of Datadog is quite useful.2. You can stream logs into it too.3. Its easier to look into metrics history4. Managing the downtime for various resources is simple.5. Visualization provided in the dashboard is quite intuitive.

1. JSON parsing of logs can't be done.2. It has a bit lack of proper documentation.3. Navigating to new areas in the dashboard can be a hassle.4. A bit overwhelming for newcomers.5. It has more customizations but less simplicity.

Able to see spikes on the dashboard , easy and fesiable

Takes more time sometimes to monitor logs

Search Filter I liked the most in Datadog. We can easily find the desired data thru search parameters and on top of that we can filter out the data by specifying a date range.

In the Search filter, we have to follow specific Datadog standards. It becomes slow when data is available in large amounts.

We were up and running in one night. I have minimal dev skills and required my dev to setup with me. Seemed really easy with even the knowledge I had and the free trial made it simple to try.

When you initially signup make sure you choose the right server to log into. That should be in BOLD.

One of the most praised features of Datadog is its comprehensive and flexible monitoring capabilities. It can collect and analyze data from various sources, such as servers, containers, databases, and cloud services, providing a unified view of the entire IT infrastructure.

Datadog pricing model, which can be relatively expensive for smaller organizations or startups

- The filter functionality is great which lets you filter out errors for quick analysis, can easily create custom dashboards.
- Great Visualizations, easy to set up dashboards/monitors with options do maths like ratios, rates, average, interval.
- It can be easily integrated with other apps like Slack to set alerts for failed jobs.
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- A slow learning curve, lack of resources on how to get useful functionality from UI or APIs.
- UI sometimes be bit slower although not bad if you've integrated with multiple external apps.

Datadog is intuitive, easy to configure, and easy to use.

The cost for Datadog is too expensive.

Ease of use and integrations. Log management is outstanding, as well as Kubernetes integration

Lack of a simple Prometheus integration. Agent configuration docs (for specifics) is sometimes hard to find

Being able to funnel AWS CloudWatch logs into Datadog made speed of deployment of Datadog incredibly fast - days instead of weeks.The log searching and faceting are extremely powerful. It's responsive, everything loads fast, and I can find single log lines in seconds.

Being able to create facets on historical data would be great.When digging into log lines, being able to navigate back to previous lines that we read through would be great too. Sometimes we're clicking around so fast that a log line is long gone. I end up copying the URL and pasting it into a doc so I can refer back to it.

Diligence, details and deep of monitoring all detail.

capturing every single details, validity of details and more importantly capability to monitor everything!!!

It is simple to setup and maintain. Plus the UI is really easy to understand.

Polling period of the alerts are not short enough. The lowest is every 5 minutes but if a site is down, 5 minutes is too long to wait to see if it is down.

Can monitor ANYTHING. Centralized place for log analysis, security monitoring, end user monitoring, custom business metrics. Report and alert.

Some items visible in the UI are not capable of being monitored. Unable to get APM for PHP working under litespeed.Improvements in alerting would be nice, better escalation, SMS integration, etc.

Easy to use and gives us the data we need to understand what is happening in our applications.

It has taken us a while to implement. Ebs support is not as intuitive as others.

Datadog provides a way of having a lot of information about your systems, clusters and infrastructure in only one site, being able to analyze valuable data for your company. It is possible to create alarms and notifications when overpassing some threshold or value, for example, when a service is down in your systems of when the CPU gets a high percentage of usage.

It integrates pretty well with tons of services and systems, such as Amazon Web Services, Apache, Nginx, several databases, and a long etcetera. Also, it is possible to send notifications to apps like Slack or Hipchat.

Datadog is not very easy to use at the beginning and it needs a little bit of investigation but it is worth to learn it.

From my opinion, with the most excellent features that Datadog has as user can track and take after logs in real time, something truly imperative to have within the case of extend is live. I usually like the idea of creating custom sees of sets of logs (with custom channels, information parsing and a parcel more) which user will share them together with the user group.

Setting it up for the first time, seems like is a little challenging which is not at all simple to use or understand all the capabilities that Datadog provides at first. Interface is challenging and occasionally a roadblock. Then, filters are not very helpful if user fields are not properly mapped.

For our AWS deployment, we use Datadog for application performance and server monitoring as well as synthetic HTTP tests . DataDog enables real-time information and measuring engineering-specific metrics and allows you to control how you trace and diagnose data. If you are looking to track the time it takes for a web hook to fire after an asynchronous request has been made, you can store the time the request has been sent in your database and when the webhook fires for that request, measure the delta and send it to DataDog. DataDog integrates with Slack, which allows for alerts on average and max thresholds.

Datadog has a mature product but features are limited, the tool feels dated and the UI is very plain.

Building Dashboards, Observability at the granular level

Terminology , need to distinguish different resources and not tag them as one

Ease of use and flexibility. Beginning teams can leverage out of the box but you can grow into this product as it is quite feature rich. The product just works.

It is so expensive that we consistently have to trim usage when not needed. Also due to this we have to justify the product constantly

I love the ease of use, the up-to-date documentation, and the product capabilities.

Support is slow and lacking, costs can get out of control fast and are not straightforward.