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Everything you read here is my own personal opinion and any code is provided "AS-IS" with no warranties.
MVP awarded 2007,2008,2009,2010
Service Manager Unleashed
Orchestrator 2012 Unleashed
Inside the Microsoft Operations Management Suite
Visualize Service Map data in Microsoft Visio
A common question in data center migration scenarios is dependencies between servers. Service Map can be very valuable in this scenario, visualizing TCP communication between processes on different servers.
Even if Service Map provides a great value we often hear a couple of questions, for example, visualize data for more than one hour and include more resources/servers in one image. Today this is not possible with the current feature set. But all the data needed is in the Log Analytics workspace, and we can access the data through the REST API 🙂
In this blog post, we want to show you how to visualize this data in Visio. We have built a PowerShell script that export data from the Log Analytics workspace and then builds a Visio drawing based on the information. The PowerShell script connects to Log Analytics, runs a query and saves the result in a text file. The query in our example lists all connections inbound and outbound for a server last week. The PowerShell script then reads the text file and for each connection, it draws it in the Visio file.
In the image below you see an example of the output in Visio. The example in the example we ran the script for a domain controller with a large number of connected servers, most likely more than the average server in a LOB application. In the example you can also see that for all connections to Azure services, we replace the server icon with a cloud icon.
Of course, you can use any query you want and visualize the data any way you want in Visio. Maybe you want to use different server shapes depending on communication type, or maybe you want to make some connections red if they have transferred a large about data.
In the PowerShell script, you can see that we use server_m.vssx and networklocations.vssx stencil files to find servers and cloud icons. These files and included in the Microsoft Visio installation. For more information about the PowerShell module used, please see VisioBot3000.
THE SOFTWARE IS PROVIDED “AS IS”, WITHOUT WARRANTY OF ANY KIND, EXPRESS OR IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY, FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM, OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE
SOFTWARE.
From Service Map to Network Security Group
Many data center migration scenarios include moving from a central firewall to multiple smaller firewalls and network security groups. A common challenge is how to configure each network security group (NSG). What should be allowed?
One way to map out which traffic to allow is using Service Map, as shown in previous blog posts. It is also possible to take it one step further, by automatically reading Service Map data from Log Analytics and building NSG rules based on the collected data.
To show an example of this, we have put together a PowerShell script. The script reads Service Map data for a specific server and builds an NSG and NSG rules based on the read data. The NSG is then attached to the server’s network adapter. Download the script here.
Of course, there are some risks with this; for example, if there is an “evil process” running on the server and communicating on the network, then there will be an NSG rule for this too. Also, the Service Map will only collect data for TCP traffic, not UDP, and the script expects the server to already exist in Azure. You will not be able to use this script to create NSG rules for servers that have not been migrated.
Thanks to Vanessa for good conversation and ideas 🙂
Disclaimer: Cloud is a very fast-moving target. It means that by the time you’re reading this post, everything described here could have been changed completely. The blog post is provided “AS-IS” with no warranties.
Visualize Service Map data in a workbook
Service Map is a feature in Azure Monitor to automatically discovers communication between applications on both Windows and Linux servers. Service Map visualize collected data in a service map, with servers, processes, inbound and outbound connection latency, and ports across any TCP-connected architecture — more information about Service Map at Microsoft Docs.
The default Service Map view is very useful in many scenarios, but there is, from time to time, a need for creating custom views and reports based on the Service Map data. Custom views and reports are created with Kusto queries and workbooks. In this blog post, we will look at some examples of a visualize Service map data in a workbook.
One of the main reasons you may want to create customer workbooks based on Service Map data is that the default Service Map view only shows one hour of data, even if more data is collected.
Below is an image of Service Map, used in VM Insight. In the figure, you can see Windows server DC00 in the center and all processes on the server that communicates on the network. On the right side of the figure, we can see servers that DC00 communicates with, grouped on network ports. It is possible to select another server, for example, DC11, and see which process on DC11 communicating with the process on DC00.
All service map data is stored in two different tables, VMproccess and VMConnection. VMComputer has inventory data for servers. VMprocess has inventory data for TCP-connected processes on servers.
Here are a few sample queries to get you started.
To list all machines that have inbound communication on port 80 last week
VMConnection
| where DestinationPort == "80"
| where Direction == "inbound"
| where TimeGenerated > now(-7d)
| distinct Computer
To list unique processes on a virtual machine, for last week
VMProcess
| where Computer == "DC21.NA.contosohotels.com"
| where TimeGenerated > now(-7d)
| summarize arg_max(TimeGenerated, DisplayName, Description, Computer) by ExecutableName
To list all unique communication for a server, for last week
VMProcess |VMConnection | where Computer == "DC21.NA.contosohotels.com" | where TimeGenerated > now(-7d) | summarize arg_max(TimeGenerated, Computer, Direction, ProcessName) by RemoteIp, DestinationPort
To list all communication between two IP addresses
VMConnection
| where (SourceIp == "10.1.2.20" or SourceIp == "10.3.1.20") and (DestinationIp == "10.1.2.20" or DestinationIp == "10.3.1.20")
| where TimeGenerated > now(-7d)
| summarize arg_max(TimeGenerated, SourceIp, DestinationIp, Direction, ProcessName) by DestinationPort
With workbooks, you can create dynamic reports to visualize collected data. This is very useful in migration scenarios when building network traffic rules or needs to see dependencies between servers quickly. The picture below shows an example Workbook (download here) showing all traffic for a specific server and a summary (total MB) of network traffic per network port.
Return data only during office hours and workdays
Today I want to share a log query that only returns logs generated between 09 and 18, during workdays. The example is working with security events, without any filters. To improve query performances it is strongly recommended to add more filters, for example, event ID or account.
6.00:00:00 means Saturday and 7.00:00:00 means Sunday 🙂
let startDateOfAlert = startofday(now());
let StartAlertTime = startDateOfAlert + 9hours;
let StopAlertTime = startDateOfAlert + 18hours;
SecurityEvent
| extend localTimestamp = TimeGenerated + 2h
| extend ByPassDays = dayofweek(localTimestamp)
| where ByPassDays <> ‘6.00:00:00’
| where ByPassDays <> ‘7.00:00:00’
| where localTimestamp > StartAlertTime
| where localTimestamp < StopAlertTime
| order by localTimestamp asc
Visualize alerts on Azure dashboard
A common ask is how to visualize alerts from Azure Monitor on an Azure dashboard. Publishing data, including alerts, from Azure Monitor, can be accomplished with a workbook.
With Azure Monitor workbooks, we can create interactive reports based on collected data. Read more about Workbooks at Microsoft Docs.
In this example, we visualize new active alerts on an Azure Dashboard. We start with an empty workbook and add a query tile.
Configure the query, note that we use Alerts as data source and no summary of the result. We have also configured the query to show only New Fired alerts.
Use Column Settings to hide columns that should not be displayed.
Once we are happy with the look of the result, we can click PIN, and pin the panel to a dashboard. When in Edit mode of a tile, we can pin that specific tile. We can also use pin in the top toolbar to pin all parts of a workbook to a dashboard.
Monitoring Windows services with Azure Monitor
Another question we are asked regularly is how to use the Azure Monitor tools to create visibility on Windows service health. One of the best options for monitoring of services across Windows and Linux leverages off the Change Tracking solution in Azure Automation.
The solution can track changes on both Windows and Linux. On Windows, it supports tracking changes on files, registry keys, services, and installed software. On Linux, it tracks changes to files, software, and daemons. There are a couple of ways to onboard the solution, from a virtual machine, Automation account, or an Azure Automation runbook. Read more about Change tracking and how to onboard at Microsoft Docs.
This blog post will focus on monitoring of a Window service, but the concept works the same for Linux daemons.
Changes to Windows Services are collected by default every 30 minutes but can be configured to be collected down to every 10 seconds. It is important that the agent only track changes, not the current state. If there is no change, then there is no data sent to Log Analytics and Azure Automation. Collecting only changes optimizes the performance of the agent.
Query collected data
To list the latest collected data, we can run the following query. Note that we use “let” to set offset between UTC (default time zone in Log Analytics) and our current time zones. An important thing to remember is what we said earlier; only changes are reported. In the example below, we can see that at 2019-07-15 the service changed state to running. But after this record, we have no information. If the VM suddenly crashes, there is a risk no “Stopped” event will be reported, and from a logging perspective, it will look like the service is running.
It is therefore important to monitoring everything from a different point of views, for example, in this example also monitor the heartbeat from the VM.
let utcoffset = 2h; // difference between local time zone and UTC
ConfigurationData
| where ConfigDataType == "WindowsServices"
| where SvcDisplayName == "Print Spooler"
| extend localTimestamp = TimeGenerated + utcoffset
| project localTimestamp, Computer, SvcDisplayName, SvcState
| order by localTimestamp desc
| summarize arg_max(localTimestamp, *) by SvcDisplayName
Configure alert on service changes
As with other collected data, it is possible to configure an alert rule based on service changes. Below is a query that can be used to alert if the Print Spooler service is stopped. For more steps how to configure the alert, see Microsoft Docs.
ConfigurationChange
| where ConfigChangeType == "WindowsServices" and SvcDisplayName == "Print Spooler" and SvcState == "Stopped"
You may be tempted to use a query to look for Event 7036 in the Application log instead, but there are a few reasons why we would recommend you use the ConfigurationChange data instead:
- To be able to alert on Event 7036, you will need to collect informational level events from the Application log across all Windows servers, which becomes impractical very quickly when you have a larger number of Virtual Machines
- It requires more complex queries to alert on specific services
- It is only available on Windows servers
Workbook report
With Azure Monitor workbooks, we can create interactive reports based on collected data. Read more about Workbooks at Microsoft Docs.
For our service monitoring scenario, this is a great way to build a report of current status and a dashboard.
The following query can be used to list the latest event for each Windows service on each server. With the “case” operator, we can display 1 for running services and 0 for stopped services.
let utcoffset = 2h; // difference between local time zone and UTC
ConfigurationData
| where ConfigDataType == “WindowsServices”
| extend localTimestamp = TimeGenerated + utcoffset
| extend Status = case(SvcState == “Stopped”, “0”,
SvcState == “Running”, “1”,
“NA”
)
| project localTimestamp, Computer, SvcDisplayName, Status
| summarize arg_max(localTimestamp, *) by Computer, SvcDisplayName
1 and 0 can easily be used as thresholds in a workbook to colour set cells depending on status.
Workbooks can also be pinned to an Azure Dashboard, either all parts of a workbook or just some parts of it.
Setting up heartbeat failure alerts with Azure Monitor
One of the questions we receive regularly is how to use the Azure Monitor components to alert on machines that are not available, and then how to create availability reports using these tools.
My colleague Vanessa and I have been looking at the best ways of achieving this in a way that those who are migrating from tools like System Center Operations Manager would be familiar and comfortable with.
As the monitoring agent used by Azure Monitor on both Windows and Linux sends a heartbeat every minute, the easiest method to detect a server down event, regardless of server location, would be to alert on missing heartbeats. This means you can use one alert rule to notify for heartbeat failures, even if machines are hosted on-prem.
Log Ingestion Time and Latency
Before we look at the technical detail, it is worth calling out the Log Ingestion Time for Azure Monitor. This is particularly important if you are expecting heartbeat missed notifications within a specific time frame. In the Log Ingestion Time article, the following query is shared, which you can use to view the computers with the highest ingestion time over the last 8 hours. This can help you plan out the thresholds for the alerting settings.
Heartbeat | where TimeGenerated > ago(8h) | extend E2EIngestionLatency = ingestion_time() - TimeGenerated | summarize percentiles(E2EIngestionLatency,50,95) by Computer | top 20 by percentile_E2EIngestionLatency_95 desc
Alerting
You can use the following query in Logs to retrieve machines that have not sent a heartbeat in the last 5 minutes:Heartbeat
| summarize LastHeartbeat=max(TimeGenerated) by Computer
| where LastHeartbeat < ago(5m)
The query, based on Heartbeat, is good for reporting and dashboarding, but often using the Heartbeat Metric in the alert rule fields gives faster results. Read more about Metrics here. To create an alert rule based on metrics, you want to target the Workspace resource still, but, in the condition, you want to use the Heartbeat metric signal:
You will now be able to configure the alert options.
- Select the computers to alert on. You can choose Select All
- Change to Less or equal to, and enter 0 as your threshold value
- Select your aggregation granularity and frequency
The best results we have found during testing is an alert within two minutes of a machine shut down, with the above settings – keeping the ingestion and latency in mind.
Using these settings, you should get an alert for each unavailable machine within a few minutes after it becomes unavailable. But, as the signal relies on the heartbeat of the agent, this may also alert during maintenance times, or if the agent is stopped.
If you need an alert quickly, and you are not concerned with an alert flood, then use these settings.
However, if you want to ensure that you only alert on valid server outages, you may want to take a few additional steps. You can use Azure Automation Runbooks or Logic Apps as an alert response to perform some additional diagnostic steps, and trigger another alert based on the output. This could replicate the method used in SCOM with a Heartbeat Failure alert and a Failed to Connect alert.
If you are only monitoring Azure Hosted virtual machines, you could also use the Activity Log to look for Server Shutdown events, using the following query:AzureActivity
| where OperationName == "Deallocate Virtual Machine" and ActivityStatus == "Succeeded"
| where TimeGenerated > ago(5m)
Reporting
Conversations about server unavailable alerts invariably lead to questions around the ability to report on Server Update/Availability. In the Logs blade, there are a few sample queries available relating to availability:
With the availability rate query by default returning the availability for monitored virtual machines for the last hour, but also providing you with an availability rate query that you can build on. This can be updated to show the availability for the last 30 days as follows:
let start_time=startofday(now()-30d);
let end_time=now();
Heartbeat
| where TimeGenerated > start_time and TimeGenerated < end_time | summarize heartbeat_per_hour=count() by bin_at(TimeGenerated, 1h, start_time), Computer | extend available_per_hour=iff(heartbeat_per_hour>0, true, false)
| summarize total_available_hours=countif(available_per_hour==true) by Computer
| extend total_number_of_buckets=round((end_time-start_time)/1h)+1
| extend availability_rate=total_available_hours*100/total_number_of_buckets
Or, if you are storing more than one month of data, you can also modify the query to run for the previous month:
let start_time=startofmonth(datetime_add('month',-1,now()));
let end_time=endofmonth(datetime_add('month',-1,now()));
Heartbeat
| where TimeGenerated > start_time and TimeGenerated < end_time
| summarize heartbeat_per_hour=count() by bin_at(TimeGenerated, 5m, start_time), Computer | extend available_per_hour=iff(heartbeat_per_hour>0, true, false)
| summarize total_available_hours=countif(available_per_hour==true) by Computer
| extend total_number_of_buckets=round((end_time-start_time)/5m)+1
| extend availability_rate=total_available_hours*100/total_number_of_buckets
These queries can be used in a Workbook to create an availability report
Note that the availability report is based on heartbeats, not the actual service running on the server. For example, if multiple servers are part of an availability set or a cluster, the service might still be available even if one server is unavailable.
Further reading
- Manage Metric Alerts
- Metric Alerts on Logs
- Agent Health Solution
- Using Azure Automation to take action on Azure Alerts
- Implement a Logic App action on an Alert
- Create Interactive Reports using Workbooks
Disclaimer: Cloud is a very fast-moving target. It means that by the time you’re reading this post, everything described here could have been changed completely. The blog post is provided “AS-IS” with no warranties.
Monitor a process with Azure Monitor
A common question when working with Azure Monitor is monitoring of Windows services and processes running on Windows servers. In Azure Monitor we can monitor Windows Services and other processes the same way; by looking at process ID as a performance counter.
Even if a process can be monitored by looking at events, it is not always a reliable source. The challenge is that there is no “active monitoring” checking if the process is running at the moment when looking at only events.
Each process writes a number of performance counters. None of these are collected by default in Azure Monitor, but easy to add under Windows Performance Counters.
The following query will show process ID for Notepad. If the Notepad process is not running, there will be no data. The alert rule, if needed, can be configured to generate an alert if zero results was returned during the last X minutes.
Perf
| where (Computer == “LND-DC-001.vnext.local”) and (CounterName == “ID Process”) and (ObjectName == “Process”)
| where InstanceName == “notepad”
| extend localTimestamp = TimeGenerated + 2h
| where TimeGenerated > ago(5m)
| project TimeGenerated , CounterValue, InstanceName
| order by TimeGenerated desc
Disclaimer:
Cloud is a very fast-moving target. It means that by the time you’re reading
this post everything described here could have been changed completely.
Note that this is provided
“AS-IS” with no warranties at all. This is not a production-ready solution for
your production environment, just an idea, and an example.
Inside Azure Management [e-book]
We are excited to announce the Preview release of Inside Azure Management is now available, with more than 500 pages covering many of the latest monitoring and management features in Microsoft Azure!
March 27, 2019] We are excited to announce the Preview release of Inside Azure Management is now available, with more than 500 pages covering many of the latest monitoring and management features in Microsoft Azure!
This FREE e-book is written by Microsoft MVPs Tao Yang, Stanislav Zhelyazkov, Pete Zerger, and Kevin Greene, along with Anders Bengtsson.
Description: “Inside Azure Management” is the sequel to “Inside the Microsoft Operations Management Suite”, featuring end-to-end deep dive into the full range of Azure management features and functionality, complete with downloadable sample scripts.
The chapter list in this edition is shown below:
- Chapter 1 – Intro
- Chapter 2 – Implementing Governance in Azure
- Chapter 3 – Migrating Workloads to Azure
- Chapter 4 – Configuring Data Sources for Azure Log Analytics
- Chapter 5 – Monitoring Applications
- Chapter 6 – Monitoring Infrastructure
- Chapter 7 – Configuring Alerting and notification
- Chapter 8 – Monitor Databases
- Chapter 9 – Monitoring Containers
- Chapter 10 – Implementing Process Automation
- Chapter 11 – Configuration Management
- Chapter 12 – Monitoring Security-related Configuration
- Chapter 13 – Data Backup for Azure Workloads
- Chapter 14 – Implementing a Disaster Recovery Strategy
- Chapter 15 – Update Management for VMs
- Chapter 16 – Conclusion
Download your copy here
Update Service Map groups with PowerShell
Service Map automatically discovers application components on Windows and Linux systems and maps the communication between services. With Service Map, you can view your servers in the way that you think of them: as interconnected systems that deliver critical services. Service Map shows connections between servers, processes, inbound and outbound connection latency, and ports across any TCP-connected architecture, with no
A common question is how to update machine groups in Service Map automatically. Last week my colleague Jose Moreno and I was worked with Service Map and investigated how to automate machine group updates. The result was a couple of PowerShell examples, showing how to create and maintain machine groups with PowerShell. You can find all the examples on Jose GitHub page. With these scripts we can now use a source, for example, Active Directory groups, to set up and update machine groups in Service Map.