Stackify Reviews

Although the decision to implement Stackify was not mine, when I took over the position, it was one of the tools that were being used by the company. We were using it for APM management, infrastructure monitoring, and log aggregation.

One of the features that we loved the most, is we've been able to create custom dashboards. The company I worked for is an umbrella company. We now have smaller departments under this particular company, each of them standing by themselves and each of them has its own independent development teams. At this center, we have three departments - we have security, infrastructure, and DevOps. Everybody keys into the offering from those three.

At a particular point, we needed to bridge the gap between the business guys and the tech guys and had to create dashboards based on metrics from Stackify for individual businesses. The business guys, in layman's terms, could see how well the infrastructure was doing and it was also a driving point for business, with the technology decisions. For example: How much money do we need to spend on which server for how long? Which of them do we need to upgrade and why? It allowed us to be able to tell that story easily since we could securely share pre-configured dashboards and the dashboard was responsive. The alerts were on point and it allowed us to succeed in that venture.

The solution is stable and reliable.

It's scalable.

The initial setup is easy.

I use Stackify for two projects. One is two companies, for nearly two years, I used. One is for exchanging Malaysia. One is in the telecom domain and device instrument platform. For those two companies, we do a performance test and identify the root cause of problems for response framing, calculations, and all those things. I use Stackify a lot. It's good for testing. I use it for identifying how many DB calls and third-party requests there are.

I use it personally.

It is very simple and very easy to configure. The best part is it shows how much response time and how many calls. I can see good usage of DB calls which made me improve my performance analysis skills on the project.

The solution is stable.

The deployment is very fast.

It adds value to code reviews. Whenever a developer has developed a feature and before pushing it can also push the stats of Stackify and check out performance metrics. Based on eh results, he can compare and approve the full request if it makes sense.

The use case for Stackify is for checking application performance. It's also used for logging purposes, particularly error logs and information logs. All information from a particular application goes to Stackify.

For example, if someone is making a request to an application then it crashes, I want to know what happened and what the root cause is, so I go to Stackify to get information about the error.

If an application is taking up so much resources, or if a particular resource power is spiking up in terms of resource utilization, I usually get the logs from Stackify.

If an application is down and my customer calls me and says he can't work with my application for whatever reason, I go to Stackify to get the URL logs.

Most of the time, an error occurs when the resource utilization on my server is very high, so I'll see where the problem lies through Stackify.

Stackify adds value to the business because it reduces the time spent on resolving customer complaints. For example, when a customer calls, and I've been working in the FinTech space for quite a while now, and in FinTech, you don't want to keep your customers or users waiting, so if someone is trying to take a loan now and there's an error, instead of waiting, if I'm going to the code to go and run a test on my local machine, I can just go straight to Stackify, then I'd get the stack trace error there right away. This way, I'd know where to limit my search, so I just go to my settings and look at the stack trace error, specifically look at the line being complained about, and then solve it. This reduces the TAT and reduces the time I'd need to spend debugging that particular issue.

If Stackify wasn't there for me to use, or if I don't have a proper logging mechanism, it means that I have to go into my code, run it locally on my system, try to reproduce the same scenario, and then if I'm find able to see it, then that's the only time I can start working on the error. Having Stackify means that I can more quickly see the stack trace error and the particular line of code that the error is coming from, so I can go back, narrow my search with that, and then just work from there, so Stackify helped in reducing the time in terms of resolving issues.

The solution also gives me knowledge in terms of the resources on my machine. For example, if the RAM on my server has gone low, Stackify lets me know because it shows me that the resource utilization is on a very high level. If resource utilization gets to a certain point such as 90 to 95 percent, it's going to freeze the application and when that happens, the users will not be able to use the application, so I can always go to Stackify to check.

When you try to send any request, you'll notice that the application will just be rolling or processing perpetually without getting any response from the server, but with Stackify, you usually get alerted on resource utilization. When your resource utilization gets to a certain level, the solution will alert you, and this is a feature my company enjoys because before it gets to that level where customers complain, Stackify will notify you of the issue and you can more quickly resolve the problem.

The solution can also take out some solutions, or it will scale horizontally, which means I need to go and add more resources, in terms of RAM. The same goes if there's a need for a CPU. Stackify, in a way, prevents you from being reactive because as soon as you get the alert from the solution, you just go and resolve the issue before it happens, or before your customers even take notice.

We use Stackify for server monitoring and application monitoring. We have several servers spread across AWS, and we run processes. Some of these processes run on Docker containers and some on Windows services. With Stackify, we can see the server utilization and proactively set alerts in case of any incidents.

There are a few valuable features. The performance dashboard and the accurate level of details are beneficial. For example, we used the solution to detect a memory leak simply by checking the performance dashboard over a range of hours when the incident occurred. Regarding performance, we can order requests by the response time. The performance tab is one of the best features with how the information is displayed. It visualizes the performance information you want to know.

In addition, we also appreciate the scoring. We can check the application score even without a reported incident. So if an application score changes, you know something is wrong.

I like how Stackify combines capabilities that otherwise required us to use separate tools. The combinations of these tools making it a lot more powerful than many of the other tools in the market.

Few examples are:

See all the logs associated with specific error

Monitor spikes in errors and and specific log search criteria

See the application performance together with the server performance but also the logs and errors trends and how they affect customer satisfaction

We became a more proactive organization, we get notified once trend is starting and can address it in working hours before customers even notice it.

We were using New Relic, but it wasn't providing us the info we wanted and it was so expensive that we couldn't afford having it on all prod servers. I've been using Stackify in a .net, Azure based webapp, the app is with high traffic subscription service, and solid services is essential.

Having the log and error data as part of the detailed trace was a tremendous help. And seeing all the logs recorded when an exception was thrown is a cool little feature.

In one case we were using Stackify to identify an issue that made the site slow occasionally, it was very hard to pin point the source of the problem. Once installed it was a very fast process and we identified the combination of issues that lead to this behavior. Having the log and error data as part of the detailed trace was a tremendous help. And seeing all the logs recorded when an exception was thrown is a cool little feature.