Google Cloud Reviews

The main requirement from my clients to Google Cloud is to reduce the on-prem footprint or to minimize the maintenance cost of the on-prem data center. Those who are looking for a scalable solution can go with Google Cloud. The main key point is to reduce the footprint of the on-prem data center in terms of purchasing servers and maintenance renewals, which can mainly focus on the hardware. To reduce the hardware footprint, we can prefer Google Cloud.

Some functions or features I really value in Google Cloud, especially for the banking sector and BFSI, is that they would want to maintain their on-prem workloads segregated with multiple data centers, while still adopting part of their workload to Google Cloud. In that case, they want to replicate or keep a secondary copy in Google Cloud. Google has tie-ups with some ISV solutions, Independent Software Vendor companies. For example, on-prem we have Pure Storage, Pure, and now Dell (formerly Dell EMC). Pure, NetApp, and Dell have tie-ups and have created custom solutions. If I want to keep my primary copy on-prem and reduce the cost or minimize my hardware footprint, I can keep my secondary copy in Google Cloud. Google has tie-ups with NetApp, Pure, and Dell, and they have created customized ISV solutions. The secondary copy can be kept in Google Cloud while the primary copy remains on-prem, so we can replicate the data. Overall, the pricing and costing factors can be reduced. Instead of deploying the whole same setup on another data center, Google is providing these kinds of solutions. Even other vendors provide solutions, but when compared with Pure and their solutions, we do not have the equivalent in Azure or AWS. It may be in the development phase for those providers. I am giving one example for setting up and configuring a DR setup in Google Cloud. Instead of keeping everything on-prem, to set up an on-prem disaster recovery, we have to purchase switches, routers, and servers, among many other things. However, to minimize the cost, we can keep it in Google Cloud. That is one option. The second point is that for workloads, at least for development and non-prod environments, we can leverage Google Cloud. We can use Google Cloud for both prod and non-prod workloads and application workloads.

Google Cloud Kubernetes support, especially GKE, is really reliable and good mainly from a microservices point of view for any product development. Google Kubernetes Engine is really reliable and it is good for product development because if you take some product, they might have to release multiple features on a release-by-release basis, adding multiple features. GKE is helping a lot with this. Earlier, we were completely in the monolithic approach because all the software and everything was clubbed and kept in one operating system. Now, we have segregated it. If I want a snapshot, I can use one node from the GKE. If I want some other feature in terms of replication-related features or OS-related features, everything I can use individual Kubernetes nodes. Whenever I want to do some enhancement or updates specific to that specific service, we can easily do it. Google is good in that regard.

Regarding potential areas of improvement for Google Cloud, considering that they are providing 300 plus services, some services could be improved. For example, if I am facing some network troubleshooting issue in GKE in Google Cloud, I have to dig deeply and enable some special logs, such as flow logs. To enable that, it is chargeable. At least for basic services, they should give end-to-end support. In terms of end-to-end support, if I am purchasing one firewall from Google and using that firewall, all firewall-related services should be free. If I want to troubleshoot something deep and perform deep troubleshooting, you have to enable some additional logs. That is not that good. If I have to enable additional logs and want to store them into Google Cloud storage, which is similar to an S3 bucket, it is again chargeable. Those kinds of things should be given as part of the package. If you take firewall, all firewall-related logs, activities, and diagnostics everything should come as one package. If you want to do some deep analysis, you have to enable these logs, and for that you have to store them in the cloud storage, which is again chargeable. We should not have those kinds of things.

Regarding additional costs, it can vary case by case. If I want to do deep analysis, I have to enable some logs, and for those logs, Google is charging. I am already paying for my virtual firewall from Google, and I am paying the cost for that. If I want to do some further troubleshooting and enable some low-level logs, they are charging for that. So these are the kinds of things I am talking about. To do very deep-level troubleshooting and enable additional logs, they will be charging. Not only Google, but all clouds are charging for this.

Functionality-wise, Google Cloud is fine. In terms of virtual machine deployment or VM instance, the functionality is good.

I have been working with Google Cloud for two years.

Regarding the stability of the product, it is the best one. I can give it an eight out of ten.

Scalability-wise, I will also give it an eight out of ten. Google Cloud is good for everything in terms of scalability.

Technical support is also good. The support mark is based on whether you have standard or premium support, and based on that they will provide the support, which is fine.

Currently, I am completely out of the PowerProtect domain and now completely into the cloud with Azure, AWS, and Google Cloud. So I am no longer working with PowerProtect, Data Domain, or Dell products.

I have quit DXC technology. I spent almost nine years with DXC. After that, I moved to LTI Mindtree, and now I am at Mindtree.

The initial setup for Google Cloud is simple.

The AutoML feature of Google Cloud is really good. Google is providing good AI features. We have been leveraging ServiceNow integration through API. Whatever knowledge base articles are stored in ServiceNow, through an ETL process (extract, transform, load), we have integrated with Google Engine through API. So if I want to get information, for example, my shift starts at 2:00 PM, and how many hours I am supposed to work, if I type in the front end through a chatbot or RIMA or anything, then we get the response. How we get the response is through Google Cloud. The Google Cloud storage talks to the Google search engine and AI search engine, and then it gets the data from ServiceNow, and then it responds to the user, such as "This is your shift time, 9 hours." We have been integrated with ServiceNow, Confluence portal, and SharePoint. It is really very helpful.

For security and IAM side, identity and access management in Google Cloud is good. In terms of roles and assignments, it comes under RBAC, which is role-based access control, and that is a very good feature. We can control at each service level and can restrict the control of the users. Only for developers, they need only read-only access for storage account or cloud storage. We can restrict the control at each service level. That is good.

Multi-cloud support in Google Cloud is good. Only a very few customers are using multi-cloud support. For example, a client has Azure Kubernetes Service and GKE. Both have been integrated using Google Anthos. Google Anthos is one of the services, and the main purpose is that we can deploy our workloads in AWS, for example, Kubernetes services and Kubernetes nodes. Similarly, I can deploy the same nodes on Google Cloud side as well with GKE. At any point in time, if my AWS whole region goes down, users can still access their workloads from GKE. To know that this goes down and the user is accessing from Google Cloud, the user means admin. Because Google is providing Anthos, there we can integrate with AWS as well as Google Cloud Kubernetes services. There we have the dashboard from where we can monitor. That is the best option. This option we do not have in AWS or Azure. Only Google has it with Anthos.

For Google BigQuery, we are using Google Cloud for Big Data purposes, and that is good. I have provided a solution for Big Data to only two to three clients on Google Cloud side. From BigQuery point of view, it is good. Google Cloud is good. I give this review an overall rating of eight out of ten.

My main use case for Google Cloud would be using the functions and the Vertex AI functionality, so mostly AI research and AI deployment.

For my AI research and deployment, I use Vertex AI to extract information from invoices that were used in my company. As the process tends to be very manual since you need to input a lot of sensitive information, I tried to develop a model and then with the help of Vertex AI, customize it and implement it in the real cloud platform within my company.

Using Vertex AI and Google Cloud for the invoice extraction project helps a lot compared to doing it manually or with other tools. It reduced a lot of hours that are usually invested in this process. The fact that it increased the time I spend, not just to handle one, but also many of them, is a big difference.

Regarding my main use cases with Google Cloud, I would also say the use case of using Cloud Functions. For example, whenever you need to use an API or perform a certain task within the platform, that was also part of the reason that I decided to use Google Cloud Functions.

The best features Google Cloud offers, in my experience, include very event-driven data, which means that all the information is centralized around what I can do with my data, from extracting, processing, and reporting. I think that flow is what makes it unique when I compare it to other products. I can also connect to other types of services, all within a safe platform.

The event-driven data flow benefits my work greatly. With this philosophy, I can actually process tons of messages or information, as I was discussing about invoices. With this communication, if there's something that seems wrong, I can get my other teams informed because it triggers a notification within the system and with personal users as well.

I find the combination of the three tools I mentioned before very valuable in Google Cloud. It's not just one item; it's many tools combined that make my work easier.

Google Cloud has positively impacted my organization, particularly in the work that a certain automated task can do when you compare it to manual work. It saves a lot of hours and a lot of resources that are put into this type of task. It's very convenient.

Regarding how many hours or resources my organization has saved since using Google Cloud for these tasks, if I were to do these activities manually per day, I can process around 10 of them, but with this function, it could be done within an hour. Of course, there's time for the building of this solution as well, but overall, when you measure this solution into production when you need to handle not 10, but 50 per week, and this could be done within one or two hours, that saves a lot of time.

I think perhaps the usability of Google Cloud could be one of the things that might get improved. In terms of not having to type the whole instruction I need to input to the system, just maybe some keywords would be helpful. I think mostly that.

Adding to the user usability of Google Cloud, I believe the type of notifications could also be provided in a better way, with more insightful information rather than just informative.

I think overall the interoperability with the different services of Google might be great, just to have some insights about that.

Google Cloud is definitely stable. That's why I say I made the right decision for Google Cloud.

Google Cloud's scalability really fulfills the scalable system that they promise because it integrates with many setups of users at the end of the day.

The customer support of Google Cloud goes pretty well. Whenever I have a doubt or any inquiry, I just reach the chat or even personal providers of Google are there to help me.

I would rate the customer support a nine on a scale of 1 to 10.

I used some on-premise database by IBM before using Google Cloud, but I think now for the one platform as Google Cloud, I definitely made the right decision.

I have seen a return on investment, as I can speak about less employment needed for this manual task, as well as time saved. As I was discussing in my previous example, one task that could be developed in a day, now it could be done in around one or two hours.

I don't handle the pricing, setup cost, and licensing type of thing. It's mostly the finances team that does that, but I think overall it is covering what we are expecting in terms of cost.

Before choosing Google Cloud, I evaluated other options, and I'd say IBM solutions.

On a scale of 1 to 10, I rate Google Cloud a nine.

I choose nine because it combines a unique set of tools that are actually helpful and impactful on my daily work.

Regarding Google Cloud's AI capabilities, I think the company is putting a great effort to preserve governance and security in terms of I get to access the metrics of roles and domains. Not everyone in my organization can actually have access to this information. Since one is the owner of this information, it's very responsible for us to have in mind.

Regarding Google Cloud's AI capabilities, I think the work done right now by that tool can actually enable organizations to build, deploy, and scale secure and reliable output. I think it's going in the right way.

My advice to others looking into using Google Cloud is to make use of all the tools that are provided. There's not just one tool for one solution; you can actually work with the solutions along.

I recommend using Google Cloud for different business cases, and if not, the Google Cloud team can also suit your needs with any product from Google as well.

My overall review rating for Google Cloud is a nine out of ten.

Private Cloud

Google

Our primary use case for Google Cloud involves infrastructure management. We host several virtual machines (VMs), manage network infrastructure, and use Google Workspace along with a few applications hosted on Google Cloud servers. We have recently started a business intelligence project and are working on using Google Looker Studio.

I find Google Cloud to be more manageable and cost-effective compared to other solutions. It offers good availability and scalability. We recently initiated a project with Google Cloud's data analytics capabilities. Although we are currently using Tableau, we are exploring the use of Google Looker Studio. The multi-regional deployments in Google Cloud have been beneficial, as we are hosted on our global headquarters cloud infrastructure, covering Europe, Middle East, and Africa regions.

Currently, there are no specific functionalities or features I would like to see improved in Google Cloud. Everything is up and running smoothly, and we are working on integrating a couple of projects, including business intelligence and AI tools. Some UI improvements or enhanced AI capabilities could be beneficial, but I do not have specific requirements at the moment.

I have been working with Google Cloud for the last six years.

High availability and scalability.

Google Cloud is highly scalable, and we have not faced any issues with its scalability. It allows us to manage resources with ease, optimizing underutilized or overutilized assets.

Google's technical support is highly expert and proficient. I would rate them very highly.

Positive

Before using Google Cloud, we hosted everything in-house. We managed our own data center, which was difficult to maintain in terms of cost and resources. This is why we switched to Google Cloud.

I was not involved in the initial deployment of Google Cloud in our environment, but I am aware that it was pretty straightforward.

The services are outsourced to another company, which provides managed services and supports us in managing Google Cloud.

This pertains to the commercial side, and I have not seen any specific measurable benefits in terms of time-saving or manpower saving.

Our pricing is centrally controlled, and I find it reasonable. Compared to buying new hardware, Google Cloud offers flexible options for scaling up or down, making it more convenient.

We did not evaluate any other solutions because our global strategy is 'Google first'.

I would recommend Google Cloud. Many friends from the IT community have discussions about cloud solutions. Some friends using AWS have been informed of the benefits of Google Cloud. When comparing AWS and Google Cloud Platform, I find Google Cloud Platform easier and more straightforward. Overall, I rate Google Cloud a ten out of ten.

Public Cloud

Google

The use case for the product is enterprise search.

Depending on the use case, BigQuery and other third-party data sources, and first-party data sources in Google. This includes Drive, Calendar, and Gmail.

It depends on the customer's use case and what they're trying to do. Most recently, it has been focused on search on data, such as semantic search on data, allowing business users to search directly on raw data stored in BigQuery.

We work primarily with BigQuery, Gemini, and Agent Space.

We mainly use Google Cloud products that are centered around Data Warehouse, specifically BigQuery, and in some cases looking at things to do with applications.

Most recently, we implemented a data science agent for querying data using natural language. Beyond that, it primarily relates to the cost effectiveness of data warehouse running costs versus competitors such as Snowflake.

Kubernetes is involved in approximately 20-30% of our projects on Google Cloud.

I would rate Google Cloud Identity for security configuration as nine or ten out of ten.

Cloud support directly is not strong, but support via partners is strong.

An area of improvement could be the release of products prior to general availability not being performant, as releasing to private preview occurs too soon before products are ready.

I suggest having more reliable third-party connectors on Agent Space as a platform.

I have been using this solution for four years.

I would rate the stability of the product a 10.

I would rate the ability to scale as a 10.

Cloud support directly is not strong, but via partners is strong.

Positive

I am not with Ancoris anymore. I am with a competitor called Datatonic.

The setup process depends on the use case and what the customer is looking to set up, but with Agent Space, it is relatively simple.

With something such as building a data warehouse, it becomes more complex.

We do not work with Microsoft as I work for a Google Cloud partner now.

Based on my personal experience, the main competitor for Google Cloud is AWS.

It depends on what the customer already has, so it is hard to make a direct comparison. They are comparable, but for anything related to AI and AI models, Google Cloud is stronger.

Our engineering teams use AutoML, though I personally do not. On a scale of one to ten, I would rate this solution as a nine.

Public Cloud

Google

We are using Google Cloud Kubernetes service. We are using Cloud Build. We are using the PostgreSQL managed service.

We are hosting our software platform on Google Cloud. We are using Kubernetes to serve our application to our customers. We are using the PostgreSQL managed service to store our data. We use Cloud Build to build our software versions.

We're not using AI or machine learning services from Google Cloud so far. We are using a separate service for that. We're using Claude Code, which is a service offered by Anthropic. This is a startup in the realm of AI agents.

Kubernetes is one of the most successful orchestration platforms to manage applications. It helps us a lot to seamlessly manage the scaling up and down of our applications and deploying the different versions of our apps, especially since we have different applications communicating with each other. Everything happens on Kubernetes in a seamless and organized way. Kubernetes is a very important part of our platform.

Identity and access management is a crucial functionality or service. It is fundamental in every cloud provider offering. It essentially helps you to manage your access to different resources and manage that in a good way. Google Cloud is good at that part.

Google Cloud is another competitor in the realm of cloud providers. I'm not sure if there is an edge I see in Google Cloud specifically. But it was actually a business choice, more than a technical one. I see it as another competitor.

Better discounting and discount offers, especially for long-running servers, would be a very good option. A localized cloud in the MENA region would also be very important for us because we are operating in the MENA. If there is a data center for Google Cloud in the region, this would help us a lot. This should be combined with good pricing. We found that there are some data centers in the region, but unfortunately they are more expensive than their counterparts in Europe. We had to be in Europe, although we are operating in the MENA region.

Overall, we have been using this solution for around two years.

Multi-cloud support is a feature I don't think any cloud provider offers because every cloud provider wants to lock in its customers. They won't be helping you integrate your application with other cloud providers. I didn't hear about something like that in Google Cloud.

I just moved to another company, and that company is using Google Cloud.

I always found that AWS is easier to use and more comprehensive. I find myself more accustomed to using AWS services than Google Cloud. I think AWS is more mature overall than Google Cloud in this area.

I didn't have the chance to start a project from scratch in Google Cloud. I'm not sure if I can judge this part. However, I did that in AWS and I found it easy and handy to do.

I'm not working with Honeycomb.

Google Cloud is a cloud provider and it's still a strong option to choose. However, I would personally prefer AWS. My overall rating for Google Cloud is seven out of ten.

Public Cloud

Google

I currently work with Google Cloud, mainly with BigQuery. I have recently started, approximately three months ago. I primarily use Google Cloud for BigQuery operations and data storage, similar to SQL servers.

The advantage we have here is that it is totally based on the cloud, so there is no maintenance required and it is straightforward to connect from different applications. With SQL servers, we need servers connected and ports to be opened. In the case of Google Cloud, these requirements are eliminated. We just need the project ID and the JSON, and we can connect from anywhere, from any application.

The most valuable aspect is that it is cloud-based and we do not need to maintain any data center. Everything is taken care of by a third party.

In terms of corporate benefits, we don't need to invest efforts in maintenance. Whatever flexibility a developer needs, Google Cloud provides that flexibility.

Since I'm working with BigQuery, I had to invest time to become familiar with the system. As I was working in SQL server previously, I had an idea that we would have a server, and inside the server, we would have a database and a separate folder for stored procedures. That hierarchy was different in Google BigQuery. If the hierarchy or similarities were the same, that would help developers more conveniently migrate from a traditional SQL server to BigQuery.

I have been using this solution for approximately three months.

My senior handled the setup, so I am not sure what is required for the setup process.

For stability, I would rate it a seven out of ten.

This solution is suitable for enterprise-level organizations, particularly in finance and healthcare domains where there is substantial data volume. It becomes really difficult for a particular company or organization to handle data centers, which is where we can leverage Google Cloud.

I am not familiar with the customer service.

Neutral

I have moved to another vendor called Power Automate.

We use Gemini for some of our projects for data extractions or summarization of data. ChatGPT from OpenAI is a serious competitor to Gemini. Other competitors include Meta's Llama.

For analytics, we are using Power BI. I have rated Google Cloud a 9 out of 10.

Public Cloud

Google

Our primary use case for Google Cloud is deploying applications. Our applications are deployed on Google Cloud, and we use it to manage our deployment process.

The most valuable features of Google Cloud for us are the integration with Kubernetes, IAM, Istio integration, and Terraform capabilities. Additionally, the overall route to live or the time to production has improved significantly. The scalability and flexibility have improved a lot. The ability to create boundaries between different parts of the application using VPCs is highly beneficial.

The logging could be improved; there's currently no intuitive way to filter logs on the Google console, especially for individuals who are not familiar with query languages. Our non-technical users find it difficult to access logs. Additionally, the user interface could be more user-friendly and intuitive compared to our previous experience with AWS.

I have been working with Google Cloud for approximately two years.

The deployment process itself takes just a few minutes, which is a significant improvement from our previous in-house deployment process. Our release window is only fifteen to twenty minutes, allowing us to do everything within that timeframe.

I have not faced any issues with the stability of Google Cloud.

We are using GKE, and I find Google Cloud to be highly scalable for our environment. If I had to rate scalability from one to ten, I would rate it a nine as we have never faced any issues with scalability.

We have consulted Google support several times, and we received a quick response. I would rate the support as a nine out of ten.

Positive

This decision was made company-wide to use Google Cloud, so I was not involved in the decision-making process, and therefore I did not evaluate any other options personally.

I find the initial setup to be between medium to above average in complexity. Our large application with multiple clusters adds to the complexity, but this is more due to our specific scenario rather than inherent complexity in Google Cloud.

Our time to production has increased, and the ease of deployment has increased, reducing the overall cost and time it usually takes to bring a functionality or feature to production.

For those looking into using Google Cloud, anticipate a significant improvement in the route to live or the time to production, along with excellent scalability and flexibility. The ability to distinguish and create boundaries between different parts of an application using VPCs makes deploying in multi-clustered environments easy. I rate the overall solution an eight out of ten.

Public Cloud

Google

My platform offers a monitoring solution for the virtual machines hosted in GCP. GCP is one of the firms that I work with. For customers who use GCP as an infrastructure service, software as a service, or platform as a service, I provide visibility to their environment by using my tool.

GCP has its own tools, and one of the services it provides alongside its hosting services or cloud services is monitoring or performance analysis for the environments they are hosting. 

It offers out-of-the-box monitoring, however, it's limited to their technology. If customers use different technologies within their environment, GCP cannot offer a full performance analysis covering all the disclosures. 

There has been a net benefit in cost saving. I provide platformized service solutions and infrastructure service solutions. Customers are mainly looking for services to save money.

In terms of Google services, providing more hypervisors would be beneficial. Currently, in my region, they don't offer many services as they have just started. They have some local instances, yet improvements are needed in the tools and offers provided to customers. I currently only use, for example, a native hybrid. VMware is not available, and other hypervisors are still not there. They need to wait on that.

I have used the solution for one year.

When discussing my reach, I would rate it six or seven out of ten.

I consider them good partners when it comes to support. It's a great relationship, though not an official partnership. Both of us provide services to our customers. So, I need some kind of partnership with entities like GCP or Microsoft.

Positive

I don't have precise information on the pricing, to be honest. As far as I know, it is a little more expensive compared to other cloud options.

Customers are mainly looking for services to save money. One of the major benefits they have is high quality. I rate technical support as high quality, so I can't give it lower than eight or nine because they have a Lookout office here. Their support is kind of high. 

Overall, I would rate the product eight out of ten.

Google

All emails are scanned for viruses or fraudulent activities. Everything is validated. The emails are also scanned to see if users share valuable customer information.

Sometimes, the solution asks why we are sending certain emails. The emails are sent once we provide the clarification.

I did not find any issues with the solution. The solution is UI-based. The tool provides recommendations based on the way we use it. It suggests how we can cost-effectively use the tool. The solution has very good availability compared to the on-premise system. Previously, we faced downtime 10% of the time. It has been reduced to 1% now. The availability has been increased.

The security features must be improved. My organization has imposed high levels of security. We take quite a long time to get the required access. I am unsure if it's because of the policies we set or the delay from the product.

I have been using the solution for the past two years.

The tool is stable.

The tool is scalable. We have almost 3000 users. When we have an on-premise solution, we usually face problems. We have faced very few issues since we moved to Google Cloud. The availability has been increased.

The setup is moderately complex. Some systems have a complex structure. Some are very straightforward. Usually, we take around two weeks after the approval to get access. We usually deploy the AML models. We require database access to build the AML models. If a new member joins the team, it takes them at least two months to get the required access. The new member sits idle for two months. After that, they start learning to deploy and work on the model. The new member is trained for six months before producing the desired outcomes.

I will recommend the solution to others. It would be good for people to get certified as a Google Professional Cloud Architect before using the tool. It would help them understand Google Cloud. Overall, I rate the solution a seven out of ten.

Our company uses the solution for big data storage such as telecom, health services, SMP, and email serial data. 

We have a relationship with a vendor in India and serve as their Google partner. We have more than one million people using the CSP and 10,000 concurrent users.

The solution works well for BigQuery and big data analysis support such as column alerts and tabular databases. 

The security is very good. 

It is very easy to scale storage or databases. 

The solution should be more configurable for high-volume databases. The managed service does not allow flexible database configurations that are needed for better filter performance. We have a TPS first-grade, high-volume database using an ERC system. We are moving to Clarity for managed services and need more configurations to support it. 

The solution could improve its management services for MongoDB.

The website's memory only allows one TB. 

I have been using the solution for four years. 

The solution is stable so stability is rated an eight out of ten. 

The scalability and availability are very high so are off the charts at a twelve out of ten. 

The technical support team is okay. Sometimes they are not helpful or the response time is not good. We need support within 24 hours but they work on dealer time so responses take three or four days. 

Support is rated a six out of ten. 

Neutral

The setup is easy with no issues. 

The pricing is rated a six out of ten. 

The solution is easier to set up and use than Azure. You need lots of technical knowledge for Azure because it is difficult to use. 

The solution is the rising star but should offer better support. 

I recommend the solution over other cloud services and rate it an eight out of ten. 

Public Cloud

Google