Announcement: Percentiles added to SPM

In the spirit of continuous improvement, we are happy to announce that percentiles have recently been added to SPM’s arsenal of measurement tools.  Percentiles provide more accurate statistics than averages, and users are able to see 50%, 95% and 99% percentiles for specific metrics and set both regular threshold-based as well as anomaly detection alerts.  We will go more into the details about how the percentiles are computed in another post, but for now we want to put the word out and show some of the related graphs — click on them to enlarge them.  Enjoy!

Elasticsearch – Request Rate and Latency

Garbage Collectors Time

Kafka – Flush Time

Kafka – Fetch/Produce Latency 1

Kafka – Fetch/Produce Latency 2

Solr Req. Rate and Latency 1

Solr – Req. Rate and Latency 2

If you enjoy performance monitoring, log analytics, or search analytics, working with projects like Elasticsearch, Solr, HBase, Hadoop, Kafka, Storm, we’re hiring planet-wide!

Announcement: Redis Monitoring in SPM

Don’t worry, we didn’t just stop at Storm monitoring and metrics while improving SPM.  We’re also happy to announce support for Redis.

Specifically, here are some of the key Redis metrics SPM monitors:

• Used Memory
• Used Memory Peak
• Used Memory RSS
• Connected Clients
• Connected Slaves
• Master Last IO Seconds Ago
• Keyspace Hits
• Keyspace Misses
• Evicted Keys
• Expired Keys
• Commands Processed
• Keys count per db
• To be expired keys count per db

Also, for all application types users can add alerting rules, heartbeat alerts, and Algolerts, as well as receive emails with performance reports for a given time period.

Enough with the words, these are what the graphs look like — click them to enlarge them:

Redis-Overview

Redis-Memory

Used memory/Used memory peak/Used memory RSS chart

Redis-Keyspace-Hits

Keyspace Hits chart

Redis-Expiring-Keys

Expiring Keys chart

Redis-Evicted-Keys

Evicted Keys chart

And we’re not done.  Watch this space for more SPM updates coming soon…

Give SPM a spin – it’s free to get going and you’ll have it up and running, graphing all your Redis metrics in 5 minutes!

If you enjoy performance monitoring, log analytics, or search analytics, working with projects like Elasticsearch, Solr, HBase, Hadoop, Kafka, Storm, we’re hiring planet-wide!

Announcement: Apache Storm Monitoring in SPM

There has been a “storm” brewing here at Sematext recently.  Fortunately this has nothing to do with the fierce winter weather many of us are experiencing in different parts of the globe — it’s actually a good kind of storm!  We’ve gotten a lot of requests to add Apache Storm support to SPM and we’re please to say that is now a reality.  SPM can already monitor Kafka, ZooKeeper, Hadoop, Elasticsearch, and more. As a matter of fact, we’ve just announced Redis monitoring, too!

Here’s why you should care:

1. SPM users can see different Storm metrics in dynamic , real-time graphs, a big improvement from the standard Storm UI which only allows some time-specific snapshots.  Isn’t it better to see trends as opposed to static snapshots?  We certainly think so.
2. SPM users can create an external link and share their charts with others (like a Mailing List or in a blog post) to get insight into problems without having to provide login credentials.  Here’s an example (you will see the chart even though you don’t know UN/PW):  https://apps.sematext.com/spm-reports/s/aQjuv5GdC1
3. SPM also provides its users with common System and JVM-related metrics like CPU usage, memory usage, JVM heap size and pool utilization, among others.  This lets you troubleshoot performance issues better by allowing you to correlate  Storm-specific metrics with common System and JVM metrics.
4. …

Here are the Storm metrics SPM can now monitor:

• Supervisors count
• Topologies count
• Supervisor total/free/used slots count
• Topology workers/executors/tasks count
• Topology spouts/bolts/state spouts count
• Bolt emitted/transferred events
• Bolt acked/executed/failed events
• Bolt executed/processed latencies
• Spout emitted/transferred events
• Spout acked/failed events
• Spout complete latency

Also important to note — users can add alerting rules for all metrics, including Algolerts and heartbeat alerts, as well as receive daily, weekly, and monthly performance reports via email.

Here are some of the graphs — click on them to see larger versions:

Overview

For observing the general state of the system

Acked-Failed Decrease

Do you see how “acked” (blue line) decreased? It may be related to some problems with resources (e.g., CPU load)

Timing-Increased

Check out this “Timing” chart: see the spike at ~13:21? It seems that something is up with the CPU (again); it might be the “pressure” from Java GC (Garbage Collector)

Start-Topology-Workers

On the first chart you can see how the counts of tasks and workers grew.  It is because a new topology (“job” in Storm terminology) started at 12:25.

Start-Topology

The same as above: you can see that between 12:00 and 12:30 Storm Supervisor was restarted (something that works on each machine inside the cluster) and topology was added after restarting.

Give SPM a spin – it’s free to get going and you’ll have it up and running, graphing all your Storm metrics in 5 minutes!

If you enjoy performance monitoring, log analytics, or search analytics, working with projects like Elasticsearch, Solr, HBase, Hadoop, Kafka, Storm, we’re hiring planet-wide!

Announcement: Logsene 0.3

SPM was not the only one being released this week.  Logsene, our machine/application log and data analytics/exploration solution saw a release as well!  Let’s see what’s new in Logsene:

• Like SPM, Logsene got a new  “native” Logsene UI to complement its existing Kibana UI.  Those who are looking for something simpler than Kibana or are not Kibana fans (such people do exist, apparently!) may prefer this new, simpler UI reminiscent of older versions of Kibana better.
• We’ve put a lot of new info up on Logsene Wiki, including how to send logs to Logsene with Logstash, how to send logs to Logsene via Syslog (syslogs/syslog-ng/rsyslog), and of course directly via Logsene’s Elasticsearch API.
• We’ve also published info about searching Logsene via Elasticsearch API, as well as searching with Kibana.
• You know how when you are troubleshooting application issues and are asking for help on public mailing lists people often ask you to share your logs so they can help you more?  You can now do that from Logsene!  You can select any number of your log events by clicking on them in Logsene’s new UI and publish them anonymously to Github Gist (see a short video)!  Once you do that you can share the Gist URL with anyone you want, such as your team or people offering their help on some mailing list.  In the upcoming release(s) we’ll let you specify you username if you want to share non-anonymously.  Do you want us to support sharing logs via any other service other than Github Gist?  Pastie?  Pastebin?  Something else?  Leave a comment!
• Just like you can select logs and “gist them”, you can export logs from Logsene in CSV format.  If you’ve always wanted to import your logs in Excel, now is your chance!
• You know how you can search Google using syntax like +requiredTerm -excludedTerm “phrase query” and such?  You can use this flexible search syntax with Logsene now.  As a matter of fact, you can use the complete Lucene search syntax in Logsene now.
• If you are like a lot of people out there who repeatedly run the same set of queries against their logs, you’ll appreciate the new Saved Queries functionality.  Like the same implies, Saved Queries you type in a query, save it, and re-run it later on without having to remember or retype it again.

If you enjoy performance monitoring, log analytics, or search analytics, working with projects like Elasticsearch, Solr, HBase, Hadoop, Kafka, Storm, we’re hiring planet-wide!

Announcement: New goodness in SPM

We don’t typically announce new SPM, Logsene, or Search Analytics releases, but yesterday’s release calls for an exception.  Logsene release deserves its own post, so we’ll post that separately.  For a quick rundown you can jump over to SPM Changelog. This blog has a bit more descriptive info.

The most visible change in SPM is the whole new, much more modern UI based on Bootstrap. Yes, we have designer(s) on our team now!  You can now much more seamlessly switch between your SPM, Logsene, and Search Analytics apps and the whole experience should feel a lot smoother.  Dashboards were previously fairly hidden, but should now gain visibility.  The “Common” part of SPM, Logsene, and Search Analytics, what we internally call “SUA”, has been radically changes to make navigation much simpler.  While we’ve made lots of UI/UX changes in this release, you’ll see us improving the UI/UX going forward, too.  Please tell us (e.g. leave a comment here) what you think about the new UI, good and bad stuff, and tell us what sort of user experience you’d like to get from SPM!  While the new UI is impossible to miss, there is more in this release:

• We’ve expanded SPM integration to Redis and Apache Storm.  SPM can now monitor both Redis and Storm and alert you on any of their metrics. This is in addition to monitoring Solr and SolrCloud, Elasticsearch, Hadoop, HBase, Kafka, ZooKeeper, Sensei, JVM, System, and Custom metrics.  Don’t forget to tell us what you want to monitor!
• More security-sensitive SPM users asked if they could hide their hostnames, which led to the new hostname aliasing/obfuscation feature.  See Can hostnames in SPM be obfuscated or customized? in SPM FAQ.  This is really handy not only because it avoids sending hostnames over the network, but because it lets you specify nice, user-friendly nicknames/aliases for them, so you know which host is which in SPM.
• When we announced Algolerts a couple of months ago we pointed out a few known kinks.  We’ve taken care of a couple of them in this release.  This boils down to being smart about recognizing regular metric variations and not confusing them with actual anomalies, as well as not missing anomalies that were until now masked by preceding anomalous patterns.
• We’ve improved the SPM Client, which now loads in a separate classloader from the application in monitors when launched in embedded mode.  This avoids any potential conflicts between libraries included in the SPM Client and those loaded in the monitored application’s process.

If you enjoy performance monitoring, log analytics, or search analytics, working with projects like Elasticsearch, Solr, HBase, Hadoop, Kafka, Storm, we’re hiring planet-wide!

What’s New in SPM 1.13.0

We pushed a new SPM release to production this morning and it’s loaded with goodies.  Here is a quick run-down of a few interesting ones. The slightly longer version can be found in SPM Changelog:

PagerDuty integration. If you are a PagerDuty user, your alerts from SPM can now go to your PagerDuty account where you can handle them along with all your other alerts.

Ruby & Java libraries for Custom Metrics.  We open-sourced sematext-metrics, a Ruby gem for sending Custom Metrics to SPM as well as sematext-metrics for doing the same from Java.

Coda Metrics & Ruby Metriks support.  We open-sourced sematext-metrics-reporter, a Coda’s Metrics reporter for sending Custom Metrics to SPM from Java, Scala, Clojure, and other JVM-based apps, and we’ve done the same for Metriks – the Ruby equivalent of Coda’s Metrics library.

Puppet metrics. We begged James Turnbull to marry Puppet and SPM and write a Puppet report processor thats sends each of the metrics generated by a Puppet run to SPM, which he did without us having to buy him drinks….yet.

Performance.  We’ve done a bit of work in the layer right behind the UI to make the UI a little faster.

CentOS 5.x support.  Apparently a good number of people still use CentOS 5.x, so we’ve update the SPM client SPM to work with it.  You can grab from SPM Client page.

– @sematext

What’s new in SPM 1.12.0

We’ve been very heads down since our last official release of SPM, as you can see from our SPM Changelog.  Here is some more info about new things you’ll find in SPM:

• For the impatient – there is now a demo user (click on this and you will be logged in as the demo user).  This lets you into both SPM and Search Analytics even if you don’t have an account, so you can see  reports for various types of SPM Apps as well as what Search Analytics reports are like.

• The SPM Client (aka SPM Agent) can now be installed as an RPM or a Debian packages – check SPM client page.  Until now, the installer was completely written in Bash, but using Jordan Sissel’s fpm we were able to easily put together SPM Client packages.  Moreover, you can now easily install SPM Client on Redhat, CentOS, Fedora, Debian, Ubuntu, SuSE, Amazon Linux AMI, and maybe some other smaller distros we didn’t get to test.  If you try it on some  other distro, please let us know if it worked or if you had issues, so we can help!

• SPM for Hadoop can now be used to monitor Hadoop HDFS, MapReduce, and YARN clusters.  We have tested SPM for Hadoop with CDH (Cloudera Hadoop Distribution), but it should work just as well with Apache Hadoop, or HDP (Hortonworks Data Platform), and perhaps MapR’s Hadoop distros as well.  Of course, you can use the same Sematext Apps account to monitor any number of your clusters and clusters of any type, so it’s extremely easy to switch from looking at your Hadoop metrics, to HBase metrics, to Solr or ElasticSearch metrics.  We are working on expanding monitoring support to other technologies.  Tell us what you would like SPM to monitor for you!

• SPM users already loved the Overview panel in SPM (see Screenshots), but the new Custom Dashboards are even cooler!  Here are some things to know about the new SPM Dashboards:
  • You can have any number of them and you can name them – there are no limits
  • You can add any SPM graph to any of your existing dashboards and it’s super easy to create a new dashboard when you realize you want the graph you are looking at on a new dashboard
  • You can drag and drop dashboard panels wherever you want, resize them, and they’ll nudge other panels around and snap onto a neat, invisible grid
  • You can add graphs from any number of different SPM applications to the same dashboard.  So you can create a dashboard that has all the graphs that are important to you and your application(s), and combine metrics from different (types of) apps in a single view.  For example, you can have a dashboard that shows the number of HBase compactions as well as ElasticSearch index merging stats on the same dashboard, right next to each other.
  • Not only can you mix and match graphs from different SPM Apps on the same dashboard, but if you are a Search Analytics user you can also have Search Analytics graphs right next to your performance graphs!  That’s powerful!
  • And for those who discovered Logsene, our soon to be announced Data & Log Analytics service, you can imagine how eventually SPM & Logsene will be able to play together and share the same dashboards!

• SPM Clients do a good job of gathering server and application metrics for applications covered by SPM.  But what if you want to monitor something else in addition to what SPM collects and graphs?  Or what if you want to feed in some non-performance data – say some user engagement metrics or some other Business KPI?  Well, you can do that now!  We’ve added Custom Metrics to all plans and this addition is free of charge!  And guess what?  You can build graphs with your custom metrics and put them on any and however many of your Dashboards you want, so you could potentially have your KPIs be shown next to your Performance Metrics, next to your Log Analytics, next to your Search Analytics!

• To help SPM users feed custom metrics into SPM we’ve released and open-sourced the first Sematext Metrics library for Java, with libraries for other languages to follow. Improvements welcome, pull requests welcome, support for other languages super welcome!

• You can now share, tweet, and embed your SPM graphs as you please.  Next to each icon you will see a little “share” icon that will open up a dialog window and there you can save the displayed short link, which you can tweet, or email.  You’ll also see an HTML snippet that you can copy and paste into your blog or your Wiki.  The shared or embedded widget is cool because you can select very specific filters in SPM and the shared/embedded graph will remember them.  Furthermore, you can choose to have your graph show a specific, fixed time range or, alternatively, you can choose to always show the last N minutes, or hours, or days…. This can be quite handy for sharing with team members who may not have access to SPM for one reason or another, but do want access to these graphs – think C*Os or anyone else who needs to be fed graphs and graphs, and some more graphs.

• Here is a cool and very handy feature that was suggested by George Stathis from Traackr, one of our early SPM users:  If you are a developer in charge of your application, your servers, your cluster, what happens when something breaks or just starts working poorly?  Many people turn to mailing lists to seek help from the open source community.  Experts on these mailing lists often ask for more information so they can provide better help.  Very often this information is in the form of graphs of various performance metrics.  So if you look at SPM you will see a little ambulance icon that, when clicked, puts together an email template that includes a short, public link to whichever graph’s ambulance icon you clicked on.  You can then incrementally keep adding links to other graphs to this email and, when you are ready, email it without leaving SPM.  This is incredibly easy and it makes it a breeze to put together an email that has a bunch of informative graphs in it.  This means you don’t have to go open your email client, you don’t have to type in the mailing list address, and you don’t have to jump between the email you are composing and SPM while you copy and paste links from SPM into your email client.  And while this functionality is really handy when you need help from experts and you want to give them as much information about your system as you can so they can help you better, you can also simply change where this email will get sent and send it to whoever you want.

• We listen to our user really carefully (see above!).  Some SPM users would like to keep their data longer, so we’ve added Pro Silver – a new plan with longer data retention, more metrics, more everything.

• We’ve improved SPM for ElasticSearch so it can now collect metrics even from non-HTTP nodes.

• We have made SPM Sender, the component responsible for sending all the metrics over to us for processing, more resilient and even lighter than before.

 

We want to hear what you think and what you want!  Please use comments to leave suggestions, requests, and feedback, or simply email us or tweet @sematext.

SPM Discountorama Announcement

We are happy to announce the General Availability of SPM, our performance monitoring solution for Apache Solr, ElasticSearch, HBase, SenseiDB, and Java applications, and of course all system metrics. You can also vote for what else you want SPM to monitor.  Over the last N months that we’ve been running SPM we’ve received a lot of good feedback (thanks!), a lot of words of encouragement (thanks!), and even a few nice quotes (another thanks!). Here is one from Jerry Yang, a Software Engineer at Walmart Labs: “I have been using SPM for couple of days and it has been amazing. I learned a lot about my Solr services and was able to optimize based on the results on SPM. Great work.”

Discount Codes

Since holiday season is coming up, we thought we’d offer some discounts every week between now until the end of the year.  Each of the following discounts can be used only during “its week” specified below.  There is a limit to the number of people who can use each discount, so if you want it, don’t waste too much time.  Each discount will reduce the price of SPM SaaS for 365 days after you’ve used it, which effectively means you will get discount until the end of 2013.  Note that when you register for SPM you do not need to enter your credit card information.  You also don’t need to provide it when you create the SPM application for the system you want to monitor.  And it is when you create your SPM application that you can enter the discount code.

• 20% for the remainder of this week until the end of this Sunday, December 9: NY201320
• 15% for the week of December 10, 2012: NY201315
• 10% for the week of December 17, 2012: NY201310
• 5% for the week of December 24, 2012: NY201305

Note that each discount code expires on Sunday at 00:00 UTC.

SPM Flavours

The above discounts are good for our SPM SaaS.  However, if you’d rather run SPM on your own servers, we do offer SPM on Premises – please get in touch if you are interested in the on premises version.  You can also vote for SPM SaaS vs. On Premise and that way tell us which version you prefer or want.

SPM Plans

There are a few different subscription plans available in SPM SaaS:

• Basic plan that is free and shows the last 30 minutes of performance data
• Standard plan that shows the last 30 days of data and costs $0.035/server/hour
• Pro plan that shows the last 60 days of performance data and costs $0.070/server/hour

If you have not used SPM before, here is what you can expect to see – click on the image to see a large, non-fuzzy version:

We hope you will find SPM useful and fun to use.  We are always looking for feedback – just email spm-support@sematext.com or ping @sematext and tell us what you like or don’t like about SPM.