Coming soon! Our webinar just ended. Check back soon to watch the video.
Webinar Date: 2018-08-23 08:00:00 (Pacific Time)
In this training, Margo will share with you Chronograf, the user interface component of the TICK Stack. You will learn on how to set up Chronograf, building your first set of dashboards, creating TICK scripts, setting alerts, and finally how to monitor and manage your InfluxData installation. Finally a brief overview of how to set up multi-user Chronograf will be discussed.
Watch the webinar “Chronograf and Dashboarding” by filling out the form and clicking on the download button on the right. This will open the recording.
Here is an unedited transcript of the webinar “Chronograf and Dashboarding.” This is provided for those who prefer to read than watch the webinar. Please note that the transcript is raw. We apologize for any transcribing errors.
• Chris Churilo: Director Product Marketing, InfluxData
• Margo Schaedel: DevRel, InfluxData
Chris Churilo 00:00:12.434 All right. I think everything’s good now. So good morning everybody, my name is Chris Churilo, and welcome to our training this week. Every Thursday we have technical trainings, or virtual trainings, and this week we are going to be reviewing Chronograf with one of our developer evangelist staff, Margo. And just want to remind everybody that we are recording this session. If you have any questions, please feel free to post them either in the chat or the Q & A. If you’d like to actually verbally express these questions, just raise your hand, I can unmute you. And we will make sure that we get all these questions answered before the end of the presentation. And if, for some reason, we are not able to, we will definitely post them in the community site at community.influxdata.com and get those answered. In addition, if you do have questions after, you guys all have my email address, so just feel free to send me an email and we’ll make sure that we get those answered for you, as well.
Chris Churilo 00:01:13.551 So with that, I am going to mute myself and I’m actually going to run the presentation on behalf of Margo, because we have a slight technical difficulty, so there might be a slight delay. But I will also post this presentation later on SlideShare so you’ll be able to take a review of that, as well. So with that, Margo, I’m going to pass the ball to you.
Margo Schaedel 00:01:39.069 Okay. Thanks, Chris. Good morning, everyone, or good afternoon, good evening, depending on where you are. As Chris said, I’m Margo Schaedel, and I am a developer advocate at InfluxData. And today we’ll be exploring the user-interface component of the TICK Stack, which is Chronograf. And we’ll be doing some dashboarding. So, Chris, could you just [laughter]— thanks. Okay. So what we’ll be covering today. We’ll take a look at a high-level overview of Chronograf, we’ll then briefly discuss the Chronograf architecture, and then, finally, we will learn about dashboarding within Chronograf with a demo.
Margo Schaedel 00:02:26.057 Okay. So let’s look at the Chronograf overview first. So a little bit of background about the TICK Stack, the InfluxData open-source platform that is optimized for time-series data, which consists of four components of InfluxDB, Telegraf, Kapacitor, and Chronograf. InfluxDB is our core time-series database. We are able to pull in data directly into InfluxDB or using Telegraf, which has a plug-in architecture and is, essentially, our collector agent. It can collect data and report data from various hosts. But you could still directly dump data into InfluxDB if you want to. And then, Kapacitor is our real-time stream processing engine for threshold alerting, manipulating our data, down-sampling of our data. And we can do a lot of these things through Chronograf, which is our user interface for manipulating data through Kapacitor, or visualizing our data on custom-built dashboards. So with Chronograf, we can manage our time series data and create dashboards to better understand what our data is doing.
Margo Schaedel 00:04:09.071 Can we move to the next slide? Thanks, Chris. So a little bit more about Chronograf. It was originally a closed-source project, and we just made it open-source as of November 2016. So it’s still pretty new for us. We’ve continued to add a lot of functionality and features with Chronograf, trying to release every two weeks. So we have a pretty robust product now. And it’s also really easy to get up and running. And we also currently have about 11,000 installs of it going. So people have really adopted it, and it’s become pretty popular. Within Chronograf, we can query data from InfluxDB, create dashboards to visualize our data, and define and manage alerts from Kapacitor. We also have multi-tenancy capabilities. So Chronograf can support multiple organizations, multiple users with role-based access control and private instances. And then, Chronograf also offers a number of pre-created dashboards, which coincide with the Telegraf input plug-ins that we’ve got. There are, I think, about 50 of those right now. So there’s a lot there. But our most popular use for Chronograf is dashboarding. We can create custom visualizations of all our data so that we can more intelligibly analyze our data.
Margo Schaedel 00:05:58.268 Can we move to the next one, Chris? So our main objective with Chronograf, probably the biggest one, was to create a unified experience for our users, to be able to handle all the different components of the TICK Stack within one user interface. This gives you administrative capabilities like database creation, you can manage users, and you can configure Kapacitor alerts, all in one clean space. And then, the second goal we are looking at is the deeply integrated data exploration. We really wanted a simple way to see and visualize your data, make sure that you’re looking at the correct data, make sure you’re following the right patterns. We really wanted to create a way that you can do that very easily. Also, we wanted to make sure we could do that rapidly with rapid time-to-value, since we don’t have time anymore. We wanted to make the entire experience, overall, pleasant for developers to manipulate and manage data within InfluxDB, and Kapacitor alerts with Kapacitor. And so through that, we have the query builder in Chronograf, which allows you to create queries without really having to know the Influx Query Language, and also the TICK script editor, which allows you to create Kapacitor alerts without really having to know too much about TICK script. So yeah. So those are our three major goals.
Margo Schaedel 00:07:59.630 So just to reiterate, Chronograf is open-source, so you can use it both open-source, and with InfluxDB open-source, or with InfluxEnterprise, and we offer an integrated user experience for the entire TICK Stack, trying to accomplish and reach our goals of offering administrative use cases, data exploration, being able to define our Kapacitor alerts and monitor them through dashboarding, and creating custom visualizations. So it’s very easy to see how your data is being collected.
Margo Schaedel 00:08:46.999 Okay. So how do we install Chronograf? So similar to the rest of the TICK Stack, you can download binaries at influxdata.com/downloads. And then, there is a number of documentation available for further help in getting Chronograf up and running, which is available from that link there. That brings you to the page where you can go through the getting started guide and get everything configured and connected to your Kapacitor instance and InfluxDB. It is recommended that you have all four components installed and connected, as Chronograf is designed to be used with InfluxDB and Kapacitor. So yeah, so that guide will walk you through getting all of those components set up.
Margo Schaedel 00:09:51.410 Okay. So let’s discuss a little bit more about the Chronograf architecture and how it’s connected to the other components of the TICK Stack. So if we look at this diagram here [inaudible] arrows running around everywhere, and we can pretty easily see that Chronograf has the most connection to InfluxDB and Kapacitor. Within Chronograf you’ll be able to query InfluxDB really easily with the query builder, and have those results returned in real time, and visualize them right in the user interface. And then, you can also manage and manipulate your data by defining alerts in Chronograf, Kapacitor alerts, without actually having to write out TICKscript. There’s an alert builder in Chronograf that allows you to do that in a very simple and user-friendly way. And then, you can also see your alerts in Chronograf, or you could send them out to other alerting frameworks like Slack or HipChat, which allows you to really handle processing of your data and manipulating of your data. Chronograf technically isn’t really connected to Telegraf since Telegraf is mostly an agent for collecting and reporting data to InfluxDB, and you could, conceivably, put the data in yourself directly into InfluxDB or send it over to Kapacitor.
Margo Schaedel 00:11:38.600 Okay. So I guess, before we go ahead and start the demo, we’ll go through a quick round of questions. We’ll do a bit of Q and A if anybody has any burning questions that they’d like to shout out.
Chris Churilo 00:11:53.723 So why don’t you go to the Q and A panel and read the question out loud, Margo?
Margo Schaedel 00:11:59.782 Oh, okay.
Chris Churilo 00:12:00.486 And I notice that we’ve got a question from Davide.
Margo Schaedel 00:12:04.965 Okay. So the question from Davide is: Can Chronograf dashboards and UI components be easily embedded with a custom web application? Yes, I believe that we can do this. I believe there is [inaudible] less than a year ago that you can take the graphs or the custom visualizations that you create, and then embed them into your web applications. That is possible, I believe. If Chris can verify.
Chris Churilo 00:12:41.200 Yep. Yeah, you can definitely embed them into a little frame. But more often than not, we actually, when it comes to custom dashboards within an application, maybe you have a smartphone application that you want to display this data, that’s when a lot of people just do the queries directly from InfluxDB into their custom dashboards. But if you’re using it more for kind of aggregating all your individual dashboards together, then yeah, it absolutely makes sense for you to do this and you can do that.
Margo Schaedel 00:13:17.318 Okay. I believe that’s all of them, unless anybody has any others?
Chris Churilo 00:13:23.284 Hang on. Yep, Davide says, “Yes. Thank you. Cool [laughter].” Okay. Why don’t you go ahead and get set up with your demo. And yeah, I just want to reiterate to everybody that Chronograf— go ahead and share your screen, Margo, and get your demo set up. I just want to reiterate to everybody that, yeah, Chronograf is—and you can see how tiny her screen was, so that’s why we were— I think you’re going to have to do a different kind of a share because we won’t be able to see that.
Margo Schaedel 00:13:53.539 Okay.
Chris Churilo 00:13:54.627 It’s at 25% of the screen.
Margo Schaedel 00:13:56.516 Even if I—
Chris Churilo 00:13:58.830 There we go. Now we can see. And you’re just going—
Margo Schaedel 00:14:02.139 Is that better?
Chris Churilo 00:14:02.541 –to have to—yeah.
Margo Schaedel 00:14:03.233 Or still cut off?
Chris Churilo 00:14:03.419 And you’re just going to have to move to the—there you go. That’s it. So we can see. For some reason, it looks like about a third of your right-hand screen—let’s see if that looks better.
Margo Schaedel 00:14:17.042 If I zoom out, does that help, or—?
Chris Churilo 00:14:20.373 Yep. That helps actually significantly. That’s perfect.
Margo Schaedel 00:14:23.940 Okay. So can you see—?
Chris Churilo 00:14:26.055 We seen now the bottom part with [crosstalk].
Margo Schaedel 00:14:26.957 Can you see the menu?
Chris Churilo 00:14:28.463 We can see the entire menu. When you scroll down, we lose like 20% of the menu. There you go. So this view, right now, is perfect.
Margo Schaedel 00:14:38.573 Okay. Can everybody see down here?
Chris Churilo 00:14:42.573 Yeah, but just know that we can’t see the top when you move down.
Margo Schaedel 00:14:47.466 Oh, okay. This is so bizarre.
Chris Churilo 00:14:50.582 Can you maybe zoom out a little? Just a command minus?
Margo Schaedel 00:14:55.404 Yeah, I’ve zoomed out a couple—
Chris Churilo 00:15:00.907 Okay.
Margo Schaedel 00:15:03.484 Oh, that’s so bizarre. That’s like—
Chris Churilo 00:15:06.720 Yeah, you don’t want to go too far. I think that’s good. And then, when we can’t see, we’ll just raise our hands to let you know.
Margo Schaedel 00:15:12.793 Okay, so does that—?
Chris Churilo 00:15:13.285 So if you want to scroll back to the top so we can see the top of the menu. There we go. Perfect. Now we can see at least the top. All right. I’ll stop talking.
Margo Schaedel 00:15:26.143 Okay. Yeah, just jump in if at any point you can’t see what I’m doing. Okay. So I’ve now jumped into my local instance of Chronograf. And when you first arrive, you are taken to a status page, which just shows you a newsfeed, getting started, the documentation, how your alerts are, a list of alerts. And then, from there you can use the menu bar, the nav bar, to navigate between different sections. So the host list will show you your host, so currently mine’s just on my local IP in my local machine. So if you click on your host—Telegraf already is sending—if you have Telegraf connected, Telegraf’s already sending system stats into InfluxDB, and you can see a pre-created dashboard that comes straight with Chronograf once you install it and get it up and running. And there’s a number of other plug-ins, as well, that you can install with Telegraf that you can get pre-canned dashboards up and running pretty quickly. So from there, you can take a look at—if we jump down to the configuration button, you can double check what InfluxDB source are you connected to, and if you’re not connected or if you are connected. You can delete the source. You can configure your Kapacitor instance for that InfluxDB source, or you could add new sources. So here you can just add in your connection string, name your source, if you need a username and password to access it, and then what database you’ll be connecting to. And then, you can go ahead and add it. You can add a config file, as well, here. So that shows your sources.
Margo Schaedel 00:17:40.160 In your InfluxDB admin center, this shows all the databases that you have currently, that you’re connect to with your InfluxDB source. So here I just have a number of databases that are mostly samples. You can view the retention policies for each database over here. You can create new retention policies with this button. You can create new databases. One thing with creating retention policies is they actually can have the same duration, but they do have to be uniquely named, and you do have to set a default retention policy if one is not already set. And then, that way when you’re adding data into InfluxDB, you can specify which retention policy you’d like to follow. So here you can also view what users have access to this database. You can also change permissions, which I’m currently the only user, so I either have all or nothing. But normally, you have administrative capabilities to decide who can access which sources, and view, or edit, or be able to manage the different dashboards. So you can do all that here. And then, lastly, over here they have a query section. This just shows you what ongoing queries are being sent to InfluxDB. So this is great in case there’s a query that just keeps running forever and you need to kill it, which you can do over here on the right. So that just goes through a little bit of the admin and the configuration.
Margo Schaedel 00:19:40.153 Now, let’s take a look at the Data Explorer. So here with the Data Explorer, this isn’t actually where we create our dashboards, this is an area where you can kind of play around with writing out your queries and kind of you can see a visualization of whatever queries you end of [inaudible]. Can everybody see this graph? So here I’ve just clicked on—I’m going through Telegraf as my database. I can click on CPU or any of the other measurements, and then you can click on any of the fields, and then it will automatically visualize your data if you’ve input a correct query. So up here, you can see if you’ve input correct information, you should get a success sign. Or you can also change your query up here. So you can do that. That will automatically change your query builder, as well. So yeah. So you can change that over here. You can add multiple functions to better visualize your data. And this is just a filter bar so that you can go through different measurements and tags. Here for group by, this is allowing you to group your datapoints in certain time intervals. So we can group by 10 seconds, one minute, five minutes, however you can best visualize your data. This compare button is to see a comparison of your data with a previous time interval. So for example, if you select one minute, it will shift all of your data one minute forward to show you will look—or sorry, one minute back. So this allows you to compare—perhaps you have data that came in a week ago and you want to compare the data from a week ago to the data that’s coming in now to see if there has been a significant difference. So you can do comparisons. And then, you also have a fill section here. This allows you to decide what will the graph display if there is no data coming in. If when you’ve queried, there are gaps in the data. So at the moment, I believe for null and none the graph will automatically connect. It will connect those points. So you won’t actually see gaps in your visualization.
Margo Schaedel 00:23:02.468 Up here, this is just a couple queries that are pretty common query templates. Up here at the very top, we have a very small menu bar where you can directly write data into InfluxDB, okay. You can manually enter it in if you’d like or you can upload a file, and you can specify which database you’d like to write to. So you can write data directly into InfluxDB there. Here, this shows you your auto-refresh intervals. So how often will the visualizations be updated. And then, this is your time range to show in your visualizations. Do you want to show the past hour? Do you want to show the past 6 hours or 12 hours? How big is your time range? And you can also create a custom time range, as well. Here in the Data Explorer you also have the possibility to view your data in a table format. At the moment, we can only see the table format in the Data Explorer. We haven’t added the feature yet to dashboarding, but I believe that’s coming soon. And then, you can also download a CSV of your visualization. So here we mostly use the Data Explorer as a way to test things out and see an instant visualization. And then, once you’ve kind of perfected your query, you can then go over and add it to your dashboard, or it provides an easy way to quickly take a look at your data without needing to create an entire dashboard for it.
Margo Schaedel 00:25:12.979 Okay, so let’s take a look at dashboards now. So here on the dashboards section is where you can create a new dashboard. You can also create template variables for your dashboard. So this just allows you to be able to insert various— for example, if you wanted to look at different databases, you could actually cycle through different databases if you replace the database name with a template variable. And then, you can also delete and manage your dashboards over here. So we can create a new dashboard. So when we create a new dashboard, it takes us to this page where you can edit the name of your dashboard. And it comes pre-filled with one cell ready to be visualized. You can also still manage the auto refresh and the time range here and template variables. So we can go ahead and add a graph. And here we see that we don’t have any queries, so we can go ahead and add a query, which takes us to our query builder. Which basically, it’s very similar to the query builder in the Data Explorer section. So here we can select from our database, and it’s [inaudible] retention policy. We can select a measurement, and then go ahead and select a field. We can alter the function same as before. You can also keep more than one function. And it will alter your visualization on the top part of the screen. You can, same as Data Explorer, group your time interval, and you can also edit your query up in this box up here.
Margo Schaedel 00:27:53.627 So if I were to add a bunch of random characters, if I tried to update the graph, it will show an error message. So it will say, “Okay, we were unable to query the database because your query is incorrect.” So yeah. So it will automatically update and check for you, as well. And you can also edit the queries up here. Here, additionally, you can change your visualization. So you can take a look at different types of visualizations. So we can choose a line graph, we can choose a stacked graph, step plot. So these are all a little similar. For single stat, this is showing us the most recent datapoint value that came in. There’s also the line graph with single stat, which is showing you both the single stat is still the same, it’s the most recent datapoint that’s come in. And you can take a look at bar graphs. And then, we recently added the gauge, which you can set your min and max over here, and change your colors, which is always fun, and you can add thresholds, as well, to better visualize what’s going on. Yeah, there’s a number of different things you can play around with. With the line graphs and the stacked graphs, these all have controls on the side. This is mostly for handling Y-axis manipulation, so you can change the min and the max. You can change the title for your Y axis. Excuse me. You can add prefixes to your numbers, or suffixes if you need to, change the format, and then change the [inaudible], as well. So you have a lot of control over exactly how your graph will be looking.
Margo Schaedel 00:30:23.195 Okay. So if we do that. So that takes us back to the original dashboard page. Oh, but we forgot to give it a name. So we can just add a name. Let’s just do total processes. And once it’s back in the dashboard, you can actually resize it, you can change how you want it to look, change how you want it to fit with the other cells. We can add multiple cells, and move them around, and make them take up the whole screen. And in this way you can kind of play around and have everything fit together pretty well on the page. So maybe let’s just do one more. You can change the visualization and yeah. So you can definitely play around quite a bit with creating cells in the dashboard. How are we on time? Okay. So I can show you a couple of ones that are a little bit more—so this is just a little bit more finished. And you’ll notice when you highlight over them, you’ll see the legend appears over all the graphs. So that’s pretty nice.
Margo Schaedel 00:32:17.105 I think the last thing we wanted to look at was alerting. So if you take a look at this fifth menu item, alerting. This is our Kapacitor alerting. This will just show you a history of all the alerts that you’ve gotten, which you can then filter through. As you can see, I have a ton of them. And then, you can also create alerts, as well. So here you can build alert rules or write TICK scripts. You have the option to do both. If you choose to write a TICK script, it will take you to the actual TICK script editor, which you would have to know TICK script in order to write that out. But you now also have the chance to write the TICK script and view it in the Kapacitor logs, as well. And then, you can save it up here, as well. And here you have the choice of choosing whether it’ll be stream processing or batch processing, as well as which database you want to have this alert on. Then you can also build an alert rule, which takes us to the alert rule builder. And this makes things a lot easier. You don’t have to really know TICK script as much to be able to create alerts. So you would just build out your rule here by going through each of the steps. So you would name it, and you could then choose what alert type you wanted it to be, whether it would be a threshold alert, which is if you hit a critical point or if you cross a certain boundary, it will trigger that alert relative, which is triggering alert based on a comparative time range. And then, dead man, which is if there’s been nothing, if it’s been dead, if there’s been no data. So I think the most common is probably threshold. So we can try that. And then, we can just choose what do we want to place our alert on. So we’ll just use Telegraf, for now. We can say, “CPU,” and we can say maybe, “System usage,” or “Idle usage.” And then, we can create the conditions in which we want the alert to be sent. Okay, so we can say, “Okay, if usage idle is less than 60—” well, we’re going to trigger our alerts quite a bit with that, so we can maybe change it to 50. And this shows you a brief little graph to see if your alerts have been already triggering, and to kind of know what kind of threshold you should set for that. And you can change around your time range there, as well.
Margo Schaedel 00:35:57.046 And then, down here at the bottom, our alert message, we can choose to send our alerts to other alerting frameworks. This actually has to be configured first when you configure capacitor. So you can send it through and HTTP request, TCP, or there’s other alerting frameworks like Slack, HipChat. You could log it. So you can kind of choose how you want your alerts to be sent to you. You can add in your optional alert parameters, so your URL. And then, you can add in an alert message, as well. So we can say, “CPU, idle usage is—” and then, there’s a bunch of template variables down here that you can insert. So you can choose a level. And you can show the value, you can show the time when it happened. And you can give a— yeah, there’s a couple other. There’s some ID, name, task name. You can definitely customize your messages quite a bit so that it becomes more clear. And then, you would just go back up here and save the rule. And then, you can see here that it’s been enabled. I’ve disable the others because my Slack was blowing up. But yeah, you can enable or disable them here, and delete them, as well. And you can actually click over here— if you click here, you can— sorry, wrong one.
Margo Schaedel 00:38:03.223 If you want to edit it in the TICK script editor, directly, you can actually click on edit TICK script. And so even though you built it in the alert builder, you can still come back and edit it in the TICK script editor if you would like. And I think that takes us through most everything within the Chronograf user interface.
Chris Churilo 00:38:46.388 So, Margo, we have a question in the Q and A. Can you read it out loud and take a stab at answering it?
Margo Schaedel 00:38:51.801 Yeah. Let me just get back to the—oh, there we go. Okay. So this question says: “Hello, is it possible to join data from two different databases? Suppose I have one database for detailed data and a database for an hourly summary history. Can I sketch one of them over the other?” I don’t think this is possible within Chronograf at the moment. I don’t know, Chris, if you have a better knowledge of this than I do.
Chris Churilo 00:39:47.998 Yeah. So there isn’t a way to do it today, at least as you’ve asked the question, Hassan. But I was just thinking about this as Margo was going through the demo. There’s probably some kind of workarounds that we could do to do the join in the database, but then it kind of defeats the purpose of having these two different data sets in separate databases. But I think, why don’t Margo and I give it a little bit more thought, and then we’ll post your question in the community site, and then maybe give you a couple of options in there. Because it does make sense what you’re trying to accomplish, that you’re trying to separate these things, but it does make sense that you want to be able to see a summary versus the detailed data. So thank you, Hassan. Just let us know if—I know it didn’t completely answer, but we will get that fully answered for you.
Chris Churilo 00:40:45.579 So thanks so much, Margo. I think the thing that I appreciate—there’s a couple things that I appreciate about Chronograf that I hope you guys will also appreciate. I think when I first got started with using InfluxDB, sure I can use the command line to see what data I was collecting, but this is much faster. I could just click around. It’s so much easier to use the Data Explorer to just kind of click around, make sure I’m capturing data that makes sense. In the beginning, I would confuse myself a little bit about should this be a field, should this be a tag. Does it make sense? Can I group by the data? Am I grabbing the right kind of data so that I can actually do what I want to do with it? So it’s really a quick and easy way to do that.
Chris Churilo 00:41:31.556 The other thing I want to make sure that we keep in mind is this works with the Enterprise version, as well as the open source version. So there’s no special version of Chronograf. As Margo mentioned earlier, it is complete open source. And two other things that I hear from a lot of these trainings from our users is that InfluxQL’s nice, it isn’t a standard query language, so there are some nuances that are a little bit different. So having the query builder is helpful because you don’t have to know those nuances, or even if you want to learn them, it’s a much easier way to learn them. And then, finally, I don’t know how many times people told me they love the power of Kapacitor, they just don’t want to have to learn TICK script. And so you guys saw in that rule builder you can actually build your rules, and then go in and look at the TICK script. And I think it’s a much faster way to learn if you have to be able to make use of the TICK script in a much more powerful way.
Chris Churilo 00:42:37.115 Okay. Let’s see. All right. Hassan says, “Thank you.” So yeah, we’ll definitely throw that question into community. Margo, you just started at the company late last year. And how long did it take you to actually get started with using the TICK script? Because we all say that it’s really easy, and I’ve been here quite a while, so I don’t probably offer a lot of validity to that comment, but you actually just started. So how quickly were you able to get up and running with some of your databases?
Margo Schaedel 00:43:13.656 So I think for getting Chronograf, for me, up and running, I had that up and running within an hour. When I was using it, I spent a lot of time just clicking around, which I thought was great because who doesn’t love to click around, and play around with things, and break them. But yeah, I found the user interface with Chronograf pretty easy to navigate. Because I think a lot of the different— the Data Explorer, the dashboard, building graphs in the dashboard, I think that’s pretty intuitive. And then, when I started playing around with Kapacitor and making alerting rules, that came a little bit later. But building alert rules is very simple. The documentation is great. I had a couple alert rules going within a few minutes. And then, when I was looking at the TICK script afterwards, it starts to make sense when you have it already written out for you and you can kind of study it based off of what you’ve already built. So I definitely found that a much better way to learn about TICK script instead of having to go and just write it straight out of the gate. So yeah. So I still find doing the alert builder, using that is easier than having to write the TICK script in the editor by hand. Because then, you also have to remember, “I got to make sure my syntax is correct. I got to make sure I’ve used the right terminology,” and yeah. And I think the rule builder is just a lot faster in terms of having something that timed awesome. It’s very, very quick.
Chris Churilo 00:45:20.270 Excellent. So if you have any other questions, feel free to throw them into our community site. We’d be more than happy to answer them. I want to remind everybody that we have InfluxDays New York coming up next week. And Margo’s going to be hosting one of the workshops. She’ll actually be doing a similar presentation on Chronograf. And for future trainings, Margo and I actually talked about doing some more specific dashboarding trainings, not just how to use Chronograf, but what are the optimal ways to dashboard for particular technologies. So whether it’s taking a look at the pre-canned dashboards and seeing if they’re good enough for being able to monitor your MySQL instance, or are there some other best practices that we can share with you. So we’ll be posting those pretty soon.
Chris Churilo 00:46:13.244 And let’s see. It looks like we have another open question from Chris. Chris asks, “The product has evolved significantly, and I can think of several use cases that I will prototype after the New York InfluxDays. Will either of you be in attendance? Would you suggest Mac or PC platform?” My goodness, Chris, what a perfect question [laughter]. Yes, we’re actually both going to be in attendance, as well as a number of the Chronograf engineers. So it would be so fantastic to meet with you and chat with you. And I’d recommend playing around with it before the event next Tuesday so that if you have any good questions we can definitely answer them. And suggest Mac or PC? I don’t think it matters. I mean, it’s browser-based, so as far as Chronograf goes, they both seem to work just fine. Anything to add to that, Margo?
Margo Schaedel 00:47:11.818 Yeah. I think either of them is fine. I know at InfluxDays we’ll be having a demo with install the TICK Stack on a number of different OS’s. So I think, yeah, either one should be fine.
Chris Churilo 00:47:26.241 So, Chris, play around with it, come up with some really hard questions for Margo. I want to see you actually stump her, that would be pretty cool. All right. Well, I think we had a pretty great session. This is recorded. We will post this before the end of the day. And if you can’t make InfluxDays, don’t worry. I will be also posting those videos probably a few days after the event, and you’ll be able to take a look at those, as well. And then, we will then have subsequent events in London in June, and then back in San Francisco in November. But we’re always here, so trainings every Thursdays. Going to kick back the webinar series, and that’s going to be every Tuesday starting on the 20th. We have, actually, a webinar with Landoop to take a look at their Kafka streaming solution using InfluxDB as the backend data store. So love to have you guys here, and if you have any other questions, or if you have any ideas, please just feel free to come up and chat with me. If you ever meet any of us, actually, at any of the events or any of the conferences that we attend, or feel free to go ahead and shoot us an email, and we’d be happy to oblige. With that, I want to thank Margo for an excellent demo. And I want to thank everybody for joining us today.
Margo Schaedel 00:48:51.571 Thank you very much, Chris.
Chris Churilo 00:48:52.996 Thank you. Have a safe flight home, Margo.
Margo Schaedel 00:48:55.740 Thank you.
Chris Churilo 00:48:56.690 Bye-bye.
Margo Schaedel 00:48:58.136 Bye.
Track and graph your Aerospike node statistics as well as statistics for all of the configured namespaces.
Knowing how well your webserver is handling your traffic helps you build great experiences for your users. Collect server statistics to maintain exceptional performance.
Collect and graph performance metrics from the MON and OSD nodes in a Ceph storage cluster.
Use the Dovecot stats protocol to collect and graph metrics on configured domains.
Easily monitor and track key web server performance metrics from any running HAProxy instance.
Gather metrics about the running Kubernetes pods and containers for a single host.
Collect and act on a set of Mesos statistics and metrics that enable you to monitor resource usage and detect abnormal situations early.
Gather and graph metrics from this simple and lightweight messaging protocol ideal for IoT devices.
Gather phusion passenger stats to securely operate web apps, microservices & APIs with outstanding reliability, performance and control.
The Prometheus plugin gathers metrics from any webpage exposing metrics with Prometheus format.
Monitor the status of the puppet server – the success or failure of actual puppet runs on the end nodes themselves.