|Stackify Basic||Stackify for Azure Web Apps||Stackify APM+|
|Windows & Linux monitoring (CPU, memory, network, disk, etc)|
|Servers, VMs, containers and hybrid environments||NA|
|App Metrics (Processes, perf counters, JMX, etc)||NA|
|Custom metrics (via .NET, Java & Ruby libraries)|
|Monitor web application performance & user satisfaction scores|
|Monitor key web transactions & database query performance|
|Full stack performance tracking (db, web services, cache, queues, etc)|
|Understand application behavior and dependencies|
|Inline errors in code-level trace views|
|Supported languages and frameworks||List||List||List|
Pay for use ($0.02 server/hour)
Price is based on the number of instances in your app service plan.
Pay for use ($0.055 server/hour)
|*Azure App Services allow for monitoring of basic CPU and Memory only
**Azure App Services sandbox is the environment
***Azure App Services does not allow access to this dataetc
|Free Trial||Free Trial||Free Trial|
|Aggregate and index all your logs (app logs, OS logs, web access logs)|
|Powerful full text search, field explorer & dashboards|
|Tail your logs in real-time|
|Receive alerts when new application errors occur|
|Monitor application error rates|
|Monitor logs for specific log messages|
|See all logging statements related to a specific application error|
|Supported languages and frameworks||List|
$2 for each additional 1GB
Simply go to your Account Settings page and choose Upgrade Subscription. If someone else will be upgrading your account, you can get more information here.
Of course. If you decide that Stackify isn’t for you, simply cancel anytime. You will only be billed for the amount of usage metered for the current billing period to date. We hope that you’ll give us the chance to prove our value to you before you cancel the service.
Yes. As part of our Errors & Logs product you could elect to only send us errors.
Yes. APM+ includes all of the monitoring features.
Yes, we offer a free trial. Get started for FREE!
We currently treat each OS instance as a separate server. Each AWS or Azure server is billed separately. A hypervisor with 10 VMs would be billed as 10 servers, if Stackify is installed on all 10 of them. Azure Web Apps are billed by the size of the App Service Plan.
If you are using micro services or containers please contact us to figure out pricing that works for you.
Azure Web Apps are priced based on the size of your App Service Plan, not per Web App. An App Service Plan could be 3 server instances hosting 20 Web Apps. The price would be for the 3 instances from the App Service Plan.
We bill per hour. If you have 10 servers during peak times and only 2 during low traffic times, you only pay for the extra servers for the hours they are online. If a server is offline or deleted from Stackify, you will not be billed for it.
In addition to the information found on our site, we have a wide-ranging series of videos featuring our COO. You can access them here.
I was trying to find the source of a major app issue, using Stackify within minutes I found the third party service causing it, within few more seconds I've found when things broke, and how badly it affected the users and what will happen tomorrow if I won't fix it fast. Instead of a tedious full day of work it became a simple two minutes task. Stackify paid for itself in that one saved work day.
The new APM+ solution is an incredible addition to Stackify’s log management and application monitoring solutions. It allows us to quickly and easily identify performance issues all the way down to external calls, database queries, and even individual methods. There is simply no better tool to identify performance issues that can run in production, period
My organization has recently embraced DevOps as a testing methodology and we have been searching for a tool that combines server monitoring, application insights, exception logging, and log management into one place. We previously used 3 different tools in our environment, with the development team using one set of tools, and the operations staff using another. After implementing Stackify in our environment, we have been able to use one tool for all of the above. We particularly enjoy being able to correlate errors to logs and to current performance.