Pacemaker’s Automated Alerts and Alert Reporting: No More Outages for SAP Systems on Google Cloud!

3258
Of your peers have already read this article.
6:00 Minutes
The most insightful time you'll spend today!
When critical services fail, businesses risk losing revenue, productivity, and trust. That’s why Google Cloud customers running SAP applications choose to deploy high availability (HA) systems on Google Cloud.
In these deployments Linux operating system clustering provides application and guest awareness for the application state and automates recovery actions in case of failure — including cluster node, resource or node failover or failed action.
Pacemaker is the most popular software Linux administrators use to manage their HA clusters, which includes automating notifications about events — including failover fencing and node, attribute, and resource events — and reporting on events. With automated alerts and reports, Linux administrators can not only learn about events as they happen, but they can also make sure other stakeholders are alerted to take action when critical events occur. They can even discover past events to assess the overall health of their HA systems.
Here, we break down the steps to setting up automated alerts for HA cluster events and alert reporting.
How to Deploy the Alert Script
To set up event-based alerts, you’ll need to take the following steps to execute the script.
1. Download the script file ‘gcp_crm_alert.sh’ from
https://github.com/GoogleCloudPlatform/pacemaker-alerts-cloud-logging
2. Under root user, add exec flag for the script and execute deployment with:
chmod +x ./gcp_crm_alert.sh./gcp_crm_alert.sh -d
3. Confirm that the deployment runs successfully. If it does, you will see the following INFO log messages:
In the Red Hat Enterprise Linux (RHEL) system:
gcp_crm_alert.sh:2022-01-24T23:48:30+0000:INFO:'pcs alert recipient add gcp_cluster_alert value=gcp_cluster_alerts id=gcp_cluster_alert_recepient options value=/var/log/crm_alerts_log' rc=0
In the SUSE Linux Enterprise Server (SLES):
gcp_crm_alert.sh:2022-01-25T00:13:27+00:00:INFO:'crm configure alert gcp_cluster_alert /usr/share/pacemaker/alerts/gcp_crm_alert.sh meta timeout=10s timestamp-format=%Y-%m-%dT%H:%M:%S.%06NZ to { /var/log/crm_alerts_log attributes gcloud_timeout=5 gcloud_cmd=/usr/bin/gcloud }' rc=0Now, in the event of a cluster node, resource, node failover, or failed action, Pacemaker will start the alert mechanism. For further details on the alerting agent, check out the Pacemaker Explained documentation.
How to Use Cloud Logging for Alert Reporting
Alerted events are published in Cloud Logging. Below is an example of the log record payload, where the cluster alert key-value pairs get recorded in the jsonPayload node.
{
"insertId": "ktildwg1o3fbim", "jsonPayload": { "CRM_alert_recipient": "/var/log/crm_alerts_log", "CRM_alert_attribute_name": "", "CRM_alert_kind": "resource", "CRM_alert_status": "0", "CRM_alert_rsc": "STONITH-sapecc-scs", "CRM_alert_rc": "0", "CRM_alert_timestamp_usec": "", "CRM_alert_interval": "0", "CRM_alert_node_sequence": "21", "CRM_alert_task": "start", "CRM_alert_nodeid": "", "CRM_alert_timestamp": "2022-01-25T00:17:06.515313Z", "CRM_alert_timestamp_epoch": "", "CRM_alert_desc": "ok", "CRM_alert_target_rc": "0", "CRM_alert_version": "1.1.15", "CRM_alert_attribute_value": "", "CRM_alert_node": "sapecc-ers", "CRM_alert_exec_time": "" }, "resource": { "type": "global", "labels": { "project_id": "gcp-tse-sap-on-gcp-lab" } }, "timestamp": "2022-01-25T00:17:09.662557309Z", "severity": "INFO", "logName": "projects/gcp-tse-sap-on-gcp-lab/logs/sapecc-ers%2F%2Fvar%2Flog%2Fcrm_alerts_log", "receiveTimestamp": "2022-01-25T00:17:09.662557309Z" }
To get notified of a resource event — for example, when the HANA topology resource monitor fails — you can use the following filter for the alerting definition:
jsonPayload.CRM_alert_node=("hana-venus" OR "hana-mercury") -jsonPayload.CRM_alert_status="0" jsonPayload.CRM_alert_rsc="rsc_SAPHanaTopology_SBX_HDB00" jsonPayload.CRM_alert_task="monitor" To define an alert for a fencing event, your can apply this filter: jsonPayload.CRM_alert_node=("hana-venus" OR "hana-mercury") jsonPayload.CRM_alert_kind="fencing" The fencing log entry gets recorded with warning severity to give you deeper insight, and this additional information is also helpful for more specific filtering criteria: { "insertId": "1plznskfjsxt82", "jsonPayload": { "CRM_alert_attribute_value": "", "CRM_alert_recipient": "/var/log/crm_alerts_log", "CRM_alert_rsc": "", "CRM_alert_rc": "0", "CRM_alert_timestamp_usec": "529261", "CRM_alert_desc": "Operation reboot of hana-mercury by hana-venus for crmd.2361@hana-venus: OK (ref=2a9bf814-9adf-4247-af3f-94ac254fc3ca)", "CRM_alert_target_rc": "", "CRM_alert_nodeid": "", "CRM_alert_kind": "fencing", "CRM_alert_node_sequence": "33", "CRM_alert_task": "st_notify_fence", "CRM_alert_status": "", "CRM_alert_exec_time": "", "CRM_alert_attribute_name": "", "CRM_alert_timestamp_epoch": "1643072786", "CRM_alert_version": "1.1.19", "CRM_alert_timestamp": "2022-01-25T01:06:26.529261Z", "CRM_alert_interval": "", "CRM_alert_node": "hana-mercury" }, "resource": { "type": "global", "labels": { "project_id": "gcp-tse-sap-on-gcp-lab" } }, "timestamp": "2022-01-25T01:06:27.267017052Z", "severity": "WARNING", "logName": "projects/gcp-tse-sap-on-gcp-lab/logs/hana-venus%2F%2Fvar%2Flog%2Fcrm_alerts_log", "receiveTimestamp": "2022-01-25T01:06:27.267017052Z"
} Alerts can be delivered through multiple channels, including text and email. Below is an example of an email notification for our earlier example, when we defined an alert for a HANA topology resource monitor failure:

You can write and apply filters to your log-based alerts to isolate certain types of incidents and analyze events over time. For example, the following script will surface a resource event occurring within a two-hour window on a specific date:
timestamp>="2022-01-25T00:00:00Z" timestamp<="2022-01-25T02:00:00Z"
jsonPayload.CRM_alert_kind="resource"
With the ability to analyze these logged alerts over time, determine whether event patterns warrant any action.
[SIDEBAR]
The alert script prints details in the standard output and in the log file /var/log/crm_alerts_log, and this can grow over time. We recommend that the log file is set with the Linux logrotate service in order to limit the file system space. Use the following command to create the necessary logrotate setting for the alerting log file:
cat > /etc/logrotate.d/crm_alerts_log << END-OF-FILE /var/log/crm_alerts_log { create 0660 root root rotate 7 size 10M missingok compress delaycompress copytruncate dateext dateformat -%Y%m%d-%s notifempty } END-OF-FILE [END SIDEBAR]
Tips for Troubleshooting When you first deploy your alert script, how can you tell for certain that you’ve done it correctly? Use the following commands to test it out:
In RHEL:
pcs alert show
In SLES:
sudo crm config show | grep -A3 gcp_cluster_alert
You should see the following if the script is correct:
In RHEL:
Alerts: Alert: gcp_cluster_alert (path=/usr/share/pacemaker/alerts/gcp_crm_alert.sh) Description: "Cluster alerting for hana-node-X" Options: gcloud_cmd=/usr/bin/gcloud gcloud_timeout=5 Meta options: timeout=10s timestamp-format=%Y-%m-%dT%H:%M:%S.%06NZ Recipients: Recipient: gcp_cluster_alert_recepient (value=gcp_cluster_alerts) Options: value=/var/log/crm_alerts_log In SLES:
alert gcp_cluster_alert "/usr/share/pacemaker/alerts/gcp_crm_alert.sh" \ meta timeout=10s timestamp-format="%Y-%m-%dT%H:%M:%S.%06NZ" \ to "/var/log/crm_alerts_log" attributes gcloud_timeout=5 gcloud_cmd="/usr/bin/gcloud" If the commands do not display the alerts properly, re-deploy the script.
In case there is an issue with the script, or if the Cloud Logging records are not presenting as expected, examine the script log file /var/log/crm_alerts_log. The errors and warning can be filtered with:
egrep '(ERROR|WARN)' /var/log/crm_alerts_log
Any Pacemaker alert failures will be recorded in the messages and/or Pacemaker log. To examine recent alert failures, use the following command:
egrep '(gcp_crm_alert.sh|gcp_cluster_alert)' \ /var/log/messages /var/log/pacemaker.log
Keep in mind, though, that the Pacemaker log location may be different in your system from the one in the example above.
From reactive to proactive
Your SAP applications are too critical to risk outages. The most effective way to manage high availability clusters for your SAP systems on Google Cloud is to take full advantage of Pacemaker’s alerting capabilities, so you can be proactive in ensuring your systems are healthy and available.
Learn more about running SAP on Google Cloud.
Google Introduces Cloud Career Jump Start Certification for the U.S. Underrepresented Communities

3228
Of your peers have already read this article.
3:00 Minutes
The most insightful time you'll spend today!
It’s no question that the cloud computing industry is booming and cloud experts are in high demand. In 2020, 67 percent of organizations surveyed in the IDG Cloud Computing Report added new cloud roles and functions (source).
So there are plenty of cloud jobs out there, but if you don’t have years of experience, you might find it difficult to get one. This is especially true for members of underrepresented communities, who face other kinds of systemic barriers in education and employment.
To help meet this demand and democratize opportunity, Google Cloud is introducing its first virtual Certification Journey Learning program for underrepresented communities across the United States—Cloud Career Jump Start. The program is free of charge for participants, and includes technical and professional skill development and resources with an aim to provide a readiness path to certification via the Google Cloud Associate Cloud Engineer Exam.
Google Cloud’s Certification Journey Learning Program
The program offers free access to the Google Cloud Associate Cloud Engineer training, which provides support preparations for the Certification Exam. This industry-recognized certification helps job applicants validate their cloud expertise, elevate their career, and transform businesses with Google Cloud technology. Learn more about the exam by watching the Certification Prep: Associate Cloud Engineer webinar.
Designed specifically for Computer Science or Information Systems-related majors (or relevant experience), the 12-week program offers:
- Exclusive free access to Google Cloud Associate Cloud Engineer-related training to support preparations for the Certification Exam.
- Guided progress through the certification prep training on Qwiklabs.
- Office hours hosted by Google Cloud technical experts.
- Technical workshops, including sessions with Googlers who earned cloud industry certifications and have built impactful careers in cloud tech, such as Google Cloud’s Kelsey Hightower (a Principal Developer Advocate) and Jewel Langevine (a Solution Engineer).
Earn your Associate Cloud Engineer Certification
Curious if you qualify to apply for the program? We’ve put together a guide below to help:
- What does an associate cloud engineer do? Associate Cloud Engineers deploy applications, monitor operations, and manage enterprise solutions. They also use the Google Cloud Console and the command-line interface to perform common platform-based tasks, to maintain one or more deployed solutions that leverage Google-managed or self-managed services on Google Cloud.
- Who’s eligible? We are encouraging applicants from groups that have been historically underrepresented in tech including Black, Latinx, Native American & Indigenous communities. Applicants should have six or more months of hands-on experience in a Computer Information Systems-related major, and/or relevant experience through online courses, boot camps, hackathons or internships. Although the ability to program is not required, familiarity with the following IT concepts is highly recommended: virtual machines, operating systems, storage and file systems, networking, databases, programming, and working with Linux at the command line.
How do you know if you are ready for the program?
To get an idea of what the program will cover:
- Watch the Certification Prep: Associate Cloud Engineer webinar
- Complete the Skill IQ Assessment via Pluralsight
- Review the Associate Cloud Engineer Certification Exam Guide
- Take the Associate Cloud Engineer Practice Exam
Jump start a career in cloud infrastructure and technology
Following the hands-on training, Google Cloud will offer an additional 9 months of career development resources and activities. This includes an online support community, mentoring with Googlers & partners including SADA, EPAM Systems Inc., and Slalom, resume and interviewing support from Google Recruiting & Staffing, and additional career workshops. We are also partnering with a number of Black-owned and -operated, nonprofit and cloud training organizations like Kura Labs.
Cloud certifications open doors
Want to hear more about this program from two Googlers who completed it? We asked Kelsey and Jewel to share more on how certifications helped them launch their careers in the cloud industry:
- “IT certifications introduced me to the game; opportunities and hard work helped me change it.” – Kelsey Hightower, Staff Developer Advocate, Google Cloud Platform
- “Becoming certified as a cloud computing professional combined with prayer, networking, and practice has kept me moving on my purposeful and rewarding career path as an engineer.” – Jewel Langevine, Solution Engineer, Google Cloud Solutions Studio
Kelsey and Jewel’s wisdom doesn’t end there. They play a central role in the program, sharing more about how they navigated certifications and leveraged them for success.
Apply today to Cloud Career Jump Start
The program is now live in the United States, with plans to expand to other regions in the coming months. It is completely virtual, and all training is on-demand so that participants can access their coursework anytime, anywhere via the web or mobile device. To determine whether you (or someone you know) would be a great fit for the Cloud Career Jump Start, check out our guidelines and apply.
Telehealth Improves Patient and Clinical Experiences across Continuum of Care

4906
Of your peers have already read this article.
1:30 Minutes
The most insightful time you'll spend today!
According to a National Academy of Medicine discussion paper, social determinants of health (SDoH) account for upwards of 80% of a population’s health outcomes. Breaking this down further, 50% come just from socioeconomic and physical environment factors such as education, employment, income, family and social support, community safety, air and water quality, and access to housing and transit. SDoH determine access to and quality of healthcare, and are contributors to a system of disparate access to care.


We believe that to more efficiently provide comprehensive healthcare access to more people, providers will leverage technology to blend in-person and virtual modes of care delivery.
In this article, Amwell and Google Cloud examine five ways telehealth – as part of a provider’s overall care model – can help democratize access to healthcare. (graphic url)
Remove distance as a barrier to care
8.6 million Americans live more than 30 minutes from their nearest hospital. Long drives can deter patients from seeking care or maintaining routine visits. On the flip side, 92% of Americans nationwide have access to wired broadband in the home or through mobile broadband. Therefore, having a virtual visit just a click away can help remove barriers to care, like distance.
Eliminate the risk of unnecessary exposure
Virtual care means that patients don’t have to worry about potential exposure in transit, while sitting in waiting rooms, or from direct interactions during in-person health visits. This is particularly relevant when it comes to those with chronic diseases or underlying conditions. Telehealth provides patients who may be more susceptible to diseases with access to continuous healthcare without putting them at higher risk for developing more severe symptoms. Virtual visits can occur in the comfort –and safety– of patients’ homes.
Extend access to specialized care
55% of preventable hospitalization or mortality in rural settings is due to lack of access to specialty care. With telehealth, physical proximity to specialized services–typically in urban areas–can be reduced as a limiting factor. Virtual solutions grant everyone access to top specialists, regardless of location.
Save time and money
By augmenting in-person visits with telehealth applications, providers can benefit from greater efficiencies in scheduling, helping to improve their bottom line, and add more flexibility to their workday. Meanwhile, patients can spend less on travel and childcare, limit time taken off work, and save on other costs associated with in-person visits — for a savings of $35 to $690 per visit. In a survey by the COVID-19 Healthcare Coalition, 76% of the 2,000+ patients surveyed across the US responded that transportation was removed as a barrier, 65% reported they no longer had to take time off from work for an appointment, and 67 percent reporting lower costs than an in-person visit.
Combat physician shortage and fatigue
Research shows there will be a shortage of more than 100,000 doctors by 2030. In the midst of a physician shortage, telehealth can help improve care delivery and make it more efficient, ensuring more people can still have their healthcare needs addressed. Additionally, by integrating intelligence such as case triaging along with telehealth into a virtual care model, providers can help reduce clinician burnout.
Amwell and Google Cloud are partnering to deliver transformative telehealth solutions that will make it easier for more patients to receive care and improve patient and clinician experiences across the continuum of care. One example includes embedding real-time captioning and translation services powered by Google Cloud’s AI and NLP technologies within the Amwell platform to increase health access and understanding for more people.
As physicians, we are excited that the future of healthcare will continue to blend cloud technologies like EHR-integrated telehealth platforms, AI, healthcare-trained virtual agents along with in-person care to create an integrated hybrid care model that will improve patient outcomes and unburden providers, all while expanding access to broader patient populations.
To learn more, download the whitepaper “Healthcare’s Virtual Transformation,” written in conjunction with Becker’s Hospital Review.
1: “Social Determinants of Health 101 for Health Care: Five Plus Five,” National Academy of Medicine, October 2017
12018
Of your peers have already watched this video.
3:26 Minutes
The most insightful time you'll spend today!
How L&T Financial Services Processes 95% of Motorcycle Loans in Less Than Two Minutes
L&T Financial Services is one of the largest lenders in India. India’s demonetization policy in recent years has led to a shift from cash transactions to digital payments. In 2016, the government withdrew 500 and 1000 rupee notes from circulation and encouraged a heavily cash-based population to deposit their canceled notes in banks. Financial institutions needed to pivot to a new way of doing business to stay competitive. L&T Financial Services modernized its IT infrastructure to keep up with changes and capture digital opportunities.
“Working capital is crucial to stimulate growth in rural communities. Our role as a lender is to provide access to funds. We don’t want to burden borrowers with the complexities of getting a loan. Towards this end, digitization is an important step,” says Dinanath Dubhashi, Managing Director and CEO at L&T Financial Services. “Google Cloud helps us streamline service delivery and identify the right customers. By offering the fastest processing time in the industry, we want to be the go-to lender for all customers.”
L&T Financial Services considered multiple cloud providers before choosing Google Cloud. According to Dinanath, Google Cloud understands both the need for businesses to move fast and the need for IT to modernize at different speeds. “We weren’t forced to abandon existing IT systems and migrate lock, stock, and barrel to Google Cloud on day one.”
L&T Financial Services engaged Google Cloud Professional Services to guide its digital transformation journey. The smooth migration from proof of concept to full-scale deployment on Google Cloud took a matter of months.
“Collaboration: a small idea with big opportunities. G Suite helps us connect remote branches with the head office, easily access shared files to submit and track approvals, and conduct face-to-face discussions to accelerate approval processes.”
—Dinanath Dubhashi, MD and CEO, L&T Financial Services
Digitizing the workforce with G Suite
The move to the cloud at L&T Financial Services started in 2017 when the company introduced G Suite to its 14,500 employees. The legacy email system was cumbersome to use, especially for frontline staff who need email access while they are on the road. Using Gmail, employees can connect with customers and co-workers from anywhere, on any device. Employees save time by scheduling meetings with Calendar, collaborating on Docs, and conducting video calls using Hangouts Meet.
Converting data into credit insights using BigQuery
Taking data intelligence one step further, L&T Financial Services adopts a responsible lending approach by applying algorithm-based data analytics to improve credit standards. Beyond traditional data such as credit score and credit payment history, the company also considers macro-economic indicators for risk audits. For example, a farmer’s ability to pay off the loan of his new tractor depends on a successful planting and harvest. So L&T Financial Services feeds long-term data into BigQuery and runs queries to predict loan defaults based on rainfall and crop yield.
ShareChat Builds its Diverse, Hyperlocal Social Network. Thanks to Google Cloud

9243
Of your peers have already read this article.
3:00 Minutes
The most insightful time you'll spend today!
Editor’s note: Today’s guest post comes from Indian social media platform ShareChat. Here’s the story of how they improved performance, app development, and analytics for serving regional content to millions of users using Google Cloud.
How do you create a social network when your country has 22 major official languages and countless active regional dialects? At ShareChat, we serve more than 160 million monthly active users who share and view videos, images, GIFs, songs, and more in 15 different Indian languages. We also launched a short video platform in 2020, Moj, which already supports over 80 million monthly active users.
Connecting with people in the language they understand
As mobile data and smartphones have become more affordable in India, we noticed a large new segment of people, many in rural areas, being welcomed onto the internet. However, many of them didn’t speak English, and when it comes to accessing content and information—language plays a significant role. Instead of joining other social media sites where English reigned supreme, new internet users chose to join language or dialect-specific Whatsapp groups where they felt more comfortable instead.
So, we set out to build a platform where people can share their opinions, document their lives, and make new friends, all in their native language. ShareChat simplifies content and people discovery by using a personalized content newsfeed to deliver language-specific content to the right audience.
Given the high-intensity data and high volume of content and traffic, we rely heavily on IT infrastructure. On top of that, a large number of our users rely on 2G networks to post, like, view, or follow each other. Our platform needs to deliver great experiences to people who are spread out across the country and different networks without any reduction in performance.
The right cloud partner to support future growth
ShareChat was born in the cloud—we already knew how to scale systems to serve a large customer base with our existing cloud provider. But like many companies, we struggled with over-provisioning compute and storage to accommodate unpredictable traffic and avoid running out of storage. With demand rising for local language content and an increase in online interactions in response to the COVID-19 crisis, we realized that we would need a more efficient way to scale dynamically and allocate resources as needed.
Google Cloud was a natural choice for us. We wanted to partner with a technology-first company that would make it easy (and cost-effective) to manage a strong technology portfolio that would allow us to build whatever we wanted. Google is at the forefront of technology innovation and provided everything we needed to build, run, and manage our applications (including creating an efficient DevOps pipeline to fix and release new features quickly).
We had a few issues in mind at the start of discussions with the Google Cloud team, but over time, as we got information and support from them, we realized that these were the partners we wanted in our corner when it came time to tackle our most challenging problems. In the end, we decided to take our entire infrastructure to Google Cloud.
To support millions of users, we deploy and scale using Google Kubernetes Engine. While we analyze our data using a combination of managed data cloud services, such as Pub/Sub for data pipelines, BigQuery for analytics, Cloud Spanner for real-time app serving workloads, and Cloud Bigtable for less-indexed databases. We also rely on Cloud CDN to help us distribute high-quality and reliable content delivery at low latency to our users.
We now use just half the total core consumption of our legacy environment to run ShareChat’s existing workloads.
Google Cloud delivers better outcomes at every level
By moving to Google Cloud, we saw major benefits in several key areas:
Zero-downtime migration for users
At the time of migration, we had over 70 terabytes of data, consisting of 220 tables—some of which were up to 14 terabytes with nearly 50 billion rows. Due to our data’s interdependencies, moving services over one at a time wasn’t an option for us.
Even though we were migrating such large volumes of data, we didn’t want to impact any of our customers. Latency spikes for out-of-sync data might affect message delivery. For instance, if a message or notification was delayed, we didn’t want to risk a bad user experience causing someone to abandon ShareChat.
To prepare for the move, we ran a proof-of-concept cluster for over four months to test database performance in a real-world scenario for handling more than a million queries per second. Using an open-source API gateway, we replicated our legacy data environment into Google Cloud for performance testing and capacity analysis. As soon as we were confident Google Cloud could handle the same traffic as our previous cloud environment, we were ready to execute.
Using wrappers, we were able to migrate without having to change anything in our existing application code. The entire migration of 60 million users to Google Cloud took five hours—without any data loss or downtime. Today, ShareChat has grown to 160 million users, and Google Cloud continues to give us the support we need.
Scaling globally to meet unexpected demand
We rely on real-time data to drive everything on ShareChat by tracking everything that goes on in our app—from messages and new groups to content people like or who they follow. Our users create more than a million posts per day, so it’s critical that our systems can process massive amounts of data efficiently.
We chose to migrate to Spanner for its global consistency and secondary index. Unlike our legacy NoSQL database, we could scale without having to rethink existing tables or schema definitions and keep our data systems in sync across multiple locations. It’s also cost-effective for us—moving over 120 tables with 17 indexes into Cloud Spanner reduced our costs by 30%.
Spanner also replicates data seamlessly in multiple locations in real time, enabling us to retrieve documents if one region fails. For instance, when our traffic unexpectedly grew by 500% over just a few days, we were able to scale horizontally with zero lines of code change. We were also launching our Moj video app simultaneously, and we were able to move it to another region without a single issue.
Simplifying development and deployment
On average, we experience about 80,000 requests per second (RPS) –nearly 7 billion RPS per day. That means daily push notifications sent out to the entire user base about daily trending topics can often result in a spike of 130,000 RPS in just a few seconds.
Instead of over-provisioning, Google Kubernetes Engine (GKE) enables us to pre-scale for traffic spikes around scheduled events, such as holidays like Diwali, when millions of Indians send each other greetings.
Migrating to GKE has also enabled us to adopt more agile ways of work, such as automating deployment and saving time with writing scripts. Even though we were already using container-based solutions, they lacked transparency and coverage across the entire deployment funnel.
Kubernetes features, such as sidecar proxy, allows us to attach peripheral tasks like logging into the application without requiring us to make code changes. Kubernetes upgrades are managed by default, so we don’t have to worry about maintenance and stay focused on more valuable work. Clusters and nodes automatically upgrade to run the latest version, minimizing security risks and ensuring we always have access to the latest features.
Low latency and real-time ML predictions
Even though many of our users may be accessing ShareChat outside of metropolitan areas, it doesn’t mean they’re more patient if the app loads slowly or their messages are delayed. We strive to deliver a high-performance experience, regardless of where our users are.
We use Cloud CDN to cache data in five Google Cloud Point of Presence (PoP) locations at the edge in India, allowing us to bring content as close as possible to people and speeding up load time. Since moving to Cloud CDN, our cache hit ratio has improved from 90% to 98.5%—meaning our cache can handle 98.5% of content requests.
As we expand globally, we’d like to use machine learning to reach new people with content in different languages. We want to build new algorithms to process real-time datasets in regional languages and accurately predict what people want to see. Google Cloud gives us an infrastructure optimized to handle compute-intensive workloads that will be useful to us both now—and in the future.
The confidence to build the best platform
Our current system now performs better than before we migrated, but we are continuously building new features on top of it. Google’s data cloud has provided us with an elegant ecosystem of services that allows us to build whatever we want, more easily and faster than ever before.
Perhaps the biggest advantage of partnering with Google Cloud has been the connection we have with the engineers at Google. If we’re working to solve a specific problem statement and find a specific solution in a library or a piece of code, we have the ability to immediately connect with the team responsible for it.
As a result, we have experienced a massive boost in our confidence. We know that we can build a really good system because we not only have a good process in place to solve problems—we have the right support behind us.
Learn to Access Process Metrics for Full-visibility into Software and Infrastructure behind Your Apps

3394
Of your peers have already read this article.
2:00 Minutes
The most insightful time you'll spend today!
When you are experiencing an issue with your application or service, having deep visibility into both the infrastructure and the software powering your apps and services is critical. Most monitoring services provide insights at the Virtual Machine (VM) level, but few go further. To get a full picture of the state of your application or service, you need to know what processes are running on your infrastructure. That visibility into the processes running on your VMs is provided out of the box by the new Ops Agent and made available by default in Cloud Monitoring. Today we will cover how to access process metrics and why you should start monitoring them.
Better visibility with process metrics
The data gathered by process metrics include CPU, memory, I/O, number of threads, and more, for any running processes and services on your VMs. When the Ops Agent or the Cloud Monitoring agent is installed, these metrics are captured at 60-second intervals and sent to Cloud Monitoring so you can visualize, analyze, track, and alert on them. A single VM may run tens or hundreds of processes, while you may have tens of thousands running across your fleet of VMs.
As a developer, you may only care about seeing inside a single VM to troubleshoot and identify memory leaks or the source of performance issues.
As an operator or IT Admin, you may be interested in aggregate resource consumption, building baseline views of compute, storage, and networking usage across your VM fleet. Then, when those baseline consumption levels break normal behaviors, you will know when to investigate your systems.
Built for scale and ease of use
Cloud Monitoring is built on the same advanced backend that powers metrics across Google. This proven scalability means your metrics ingestion will be supported despite the extremely high cardinality. Additionally, our agents do not require any config file changes to turn on process metric monitoring.
Lastly, our goal is to provide you the observability and telemetry data where, and when, you need it. So, like the rest of the operations suite, we deliver process metrics in the context of your infrastructure, directly in the VM admin console.

The navigation is simple. Once you have the Ops Agent or the Cloud Monitoring agent installed in your VMs:
- Go to the Compute Engine console page and click on VM Instances
- Select the VM that you want to investigate
- In the navigation menu on the top, click Observability
- Click on Metrics
- Lastly, click on Processes
In the window on the right you will see a chart and a table with all of the processes in your VM. You can also filter by time frame and sort by name or value. You do not need to do anything, other than have the agent installed, for the process to be detected and displayed.
Fleet-wide metrics monitoring
Cloud Monitoring gives you a look across your fleet of VMs so you can identify the aggregated usage of resources by processes. This level of broad, yet granular, insight can drive your decisions around which software to run or how many VMs you need to optimally power your apps and services. Admins can perform a cost-savings analysis if they determine that certain processes are slowing down the work of a large number of VMs. The larger numbers of less powerful VMs can be replaced by fewer, more capable VMs.
To get this fleet-wide view:
- Navigate to Cloud Monitoring
- Click Dashboards in the left menu
- In the All Dashboards list, click on VM Instances
- Towards the top of the window, click on Processes
This provides many charts detailing the processes running across your fleet of VMs.

Get started today
To start identifying and monitoring your process metrics, you must first install the Ops Agent, or have installed the legacy Cloud Monitoring agent. Once that is complete, the process metrics data will automatically be ingested into Cloud Monitoring and the VM admin console.
If you have any questions, or to join the conversation with other developers, operators, DevOps, and SREs, visit the Cloud Operations page in the Google Cloud Community.
More Relevant Stories for Your Company

What Are India’s Biggest Companies Doing on Google Cloud?
In the last year, there’s been an upward trend in cloud adoption in India. In fact, NASSCOM finds that cloud spending in India is estimated to grow at 30% per annum to cross the US$7 billion mark by 2022. At Google, in our conversations with customers, discussions have evolved beyond cost savings

Google Cloud’s Metric Scope Makes Multi-project Monitoring Simple
Customers need scale and flexibility from their cloud and this extends into supporting services such as monitoring and logging. Google Cloud’s Monitoring and Logging observability services are built on the same platforms used by all of Google that handle over 16 million metrics queries per second, 2.5 exabytes of logs per month, and over

How Cleartrip.com is leveraging Google Cloud to survive the slump in the travel industry
With the novel coronavirus COVID-19 sweeping across continents and fatalities climbing every day, it was only a matter of time before countries closed their borders to contain its spread. In the wake of this decision, travel and tourism, the linchpins of many economies, were among the worst affected. According to

HSBC Leverages Google Cloud to Deliver Exceptional Cx for 37 Million Customers
HSBC is the world's largest international bank that has been in existence for 150 years. HSBC is present in 70 countries, has 37 million customers and is the number one bank in trade finance or cross-border finance. HSBC is a systemically important financial institution that is heavily regulated. Rapid growth






