Our primary use case for Amazon Virtual Private Cloud involves securely hosting our application and database servers within the private data center.
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Our primary use case for Amazon Virtual Private Cloud involves securely hosting our application and database servers within the private data center.
AWS services are quite convenient and user-friendly. Specifically, Amazon DynamoDB, EKS, and security features are easy to deploy and manage directly through AWS.
It would be beneficial to introduce more managed features and enhance customization options in the product. It could be more versatile and easy to use.
We have been using Amazon Virtual Private Cloud for two to three years.
I rate the platform's stability a nine out of ten.
I rate the platform's scalability an eight out of ten. Compared to Azure and GCP, there's room for improvement, particularly in managing aspects. 70% to 80% of our users have migrated to AWS.
We provide support directly to our customers. VPC's technical support team has been helpful. Their reliability has been particularly noteworthy, as they have effectively addressed any issues we've encountered, ensuring that solutions are implemented correctly. Our experience with customer service has been mainly focused on supporting development and operational aspects, where their assistance has been invaluable.
Positive
The initial setup was challenging but simple enough. It becomes easier to grasp if you approach it with a willingness to learn. It allows for a better understanding of the underlying architecture and how it's utilized.
Our work experience has mainly been with on-premises and cloud deployments, primarily within the AWS environment.
The deployment process for Amazon VPC typically involves initial planning and design discussions to understand the customer's requirements and ensure cost optimization. This planning phase may take some time as it involves coordination with various stakeholders and team members to finalize the architecture. However, once the design is in place, the actual deployment is relatively fast and efficient, depending on the setup's complexity and the project's specific requirements.
VPC tends to offer competitive pricing compared to other services. It's optimized and provides more personalized options, making it cost-effective.
The VPC's subnetting feature has significantly impacted our network design by enhancing security measures. It provides provisions to secure our network, ensuring it is not susceptible to manipulation by external users. Additionally, we leverage other security features such as the Web Application Firewall and AWS Network Firewall to enhance protection further. It is easy to set up security groups for the product.
Integrating it with other AWS services includes configuring VPCs and defining the subnet CIDR ranges. Then, we provision both public and private subnets, with sensitive databases typically placed in the private subnets. Additionally, we utilize features such as transit gateway and security groups to enhance network security. After deploying the servers within these subnets, we host our applications and manage traffic using load balancers and auto-scaling groups. Overall, the integration allows for an isolated network environment that we can efficiently manage via routing.
I recommend introducing Amazon VPC to others as it provides an excellent entry-level understanding of cloud computing and its relevance in today's world. Setting up on-premises clusters can be challenging, but its services offer a straightforward and accessible way to begin working with cloud computing. The users can gain a basic understanding of cloud computing concepts and gradually expand their knowledge to more advanced topics.
I rate it a nine out of ten.
We're using Apache Spark primarily to build ETL pipelines. This involves transforming data and loading it into our data warehouse. Additionally, we're working with Delta Lake file formats to manage the contents.
The tool's most valuable feature is its speed and efficiency. It's much faster than other tools and excels in parallel data processing. Unlike tools like Python or JavaScript, which may struggle with parallel processing, it allows us to handle large volumes of data with more power easily.
Apache Spark could potentially improve in terms of user-friendliness, particularly for individuals with a SQL background. While it's suitable for those with programming knowledge, making it more accessible to those without extensive programming skills could be beneficial.
I have been using the product for six years.
Apache Spark is generally considered a stable product, with rare instances of breaking down. Issues may arise in sudden increases in data volume, leading to memory errors, but these can typically be managed with autoscaling clusters. Additionally, schema changes or irregularities in streaming data may pose challenges, but these could be addressed in future software versions.
About 70-80 percent of employees in my company use the product.
We haven't contacted Apache Spark support directly because it's an open-source tool. However, when using it as a product within Databricks, we've contacted Databricks support for assistance.
The main reason our company opted for the product is its capability to process large volumes of data. While other options like Snowflake offer some advantages, they may have limitations regarding custom logic or modifications.
The solution's setup and installation of Apache Spark can vary in complexity depending on whether it's done in a standalone or cluster environment. The process is generally more straightforward in a standalone setup, especially if you're familiar with the concepts involved. However, setting up in a cluster environment may require more knowledge about clusters and networking, making it potentially more complex.
The tool is an open-source product. If you're using the open-source Apache Spark, no fees are involved at any time. Charges only come into play when using it with other services like Databricks.
If you're new to Apache Spark, the best way to learn is by using the Databricks Community Edition. It provides a cluster for Apache Spark where you can learn and test. I rate the product an eight out of ten.