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Top Reasons for Higher Cloud Costs

There are several reasons why cloud costs may be higher than expected:

Resource utilization: Cloud costs are typically based on the resources used, such as the number of virtual machines, the amount of storage, or the amount of network traffic. If resource utilization is higher than expected, this can result in higher costs.

Data transfer: Many cloud providers charge for data transfer, both into and out of their services. If data transfer rates are higher than expected, this can result in higher costs.

Services and features: Some cloud services and features, such as databases, machine learning, or analytics, may carry additional charges. If these services and features are used more heavily than expected, this can result in higher costs.

Lack of cost optimization: Without proper cost optimization measures in place, it is easy for cloud costs to spiral out of control. Proper cost management and optimization strategies can help to keep costs under control.

Unforeseen events or changes: Unexpected events or changes, such as an increase in traffic or a sudden need for additional resources, can cause cloud costs to increase.

Lack of understanding of pricing models: Different cloud providers have different pricing models, and it is important to understand these models in order to properly budget for cloud costs. If there is a lack of understanding of the pricing models, this can result in higher costs.

Know how to save more on your cloud bills!: Cloud Cost Optimization Guide.

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Healthcare App in 2023

Though it's difficult to predict exactly what healthcare apps will look like in 2023, as technology and user needs are constantly evolving. However, some general trends that are likely to continue or become more important in the coming years include:

Telemedicine: The COVID-19 pandemic has accelerated the adoption of telemedicine, and it is likely that this trend will continue as patients and providers seek to minimize in-person interactions.

Personalized health: Apps may leverage machine learning and artificial intelligence to provide personalized recommendations and interventions based on an individual's unique health profile.

Integration with wearable devices: Many healthcare apps will likely integrate with wearable devices such as fitness trackers and smartwatches, allowing users to track and monitor their health data in real-time.

Remote monitoring: Apps may enable remote monitoring of patients with chronic conditions, allowing healthcare providers to track their progress and intervene when necessary.

Electronic health records: Apps may provide access to electronic health records, allowing patients to view their medical history and share it with their healthcare providers.

Population health management: Apps may be used to track and analyze population-level health data to identify trends and inform public health interventions.

Interoperability: As healthcare becomes increasingly digitized, it will be important for apps to be able to interoperate with other systems and exchange data seamlessly.

It's worth noting that the specific features and capabilities of healthcare apps will depend on the needs of the target users and the goals of the app.

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CI/CD Pipeline Example

A CI/CD pipeline aims to mitigate the risks involved in releasing the software into production.

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Application Security Tools in CI/CD Pipeline

The CI/CD process has multiple stages, and so you’ll need many security tools at each stage for continuous monitoring of apps, tracking anomalies, vulnerabilities, etc. For example, a static application security test (SAST) tool is run after a pre-commit check.

In addition, issues arising during incremental SAST testing must be resolved quickly. The challenge is the heterogeneity of these security tools and their integration issues.

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Understanding the key difference between CI & CD

Starting with a little flashback– with the traditional way of development, challenges arise when developers set up to merge all the code changes in a single integration.

Each developer working on different features writes and tests code individually, as shown in the image below. But they use long-running feature branches existing for several weeks or even months to integrate the code changes once into production. As a result, the changes in the application often conflict with similar changes made by other developers. Things become worse when deployment is done only once or infrequently.

However, modern software development demands a system where multiple developers can simultaneously work on different features of the same application and deploy changes seamlessly. Enter CI/CD.

Get more details here: https://www.simform.com/blog/ci-cd-benefits/

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What is CI/CD?

Continuous Integration

Continuous Integration is an automation strategy to solve merge conflicts arising between individual developers’ code and separate code branches. CI enables teams to build workflows capable of compiling frequent code changes, building applications, and testing the newer versions for bugs and errors. After passing through the test suite, the updates are ready for the next stage of the development process.

By frequently merging changes in a shared branch, commonly known as a trunk branch, CI offers an effective solution against merge conflicts. Also, it eliminates the need to wait until the end of the coding stage to combine separate branches, reducing the complexity of issues that may occur and making them easier to resolve.

Continuous Delivery

After the code is bug tested, it is directly sent to a shared repository, for instance, GitHub. Continuous Delivery aims to boost communication between the development and operations teams by increasing the velocity at which production-ready code is delivered. It allows operations teams to deploy applications with fewer complications.

However, without a functional CI, Continuous Delivery is less effective, and therefore, testing in CI is crucial for validating the code before release. This step prevents defective code from being pushed into production. A streamlined continuous integration/delivery process paves the way for effective continuous deployment.

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Shippable used Amazon ECS to improve continuous delivery

Shippable provides a platform for hosted testing, continuous integration, and deployment from GitHub and Bitbucket repositories. It has two parts, the first one is continuous integration, and the second is continuous delivery.

Combining different services, the Shippable platform allows developers to build, test, and deploy applications. Shippable built the CI/CD platform with a microservice architecture using Docker containers on Amazon EC2. However, the docker solution was hard to scale and had configuration issues.

The engineering team at Shippable spent 60-80% of their time maintaining the infrastructure and container orchestration. Apart from the infrastructure management, monitoring extensive logs and managing Elasticsearch was time-consuming.

Shippable considered several open-source orchestration tools like Apache Mesos and Kubernetes. However, these tools were not the right fit as they also needed significant engineering time. So, Shippable chose Amazon ECS.

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The tenancy models are based on the fundamental components of a SaaS application – the tenants. Every single customer utilizing a SaaS platform is considered a tenant, and they get their access rights by paying a subscription fee.

Do note that your tenancy model does not affect your application performance. Instead, it is to meet consumer demands, provide flexible solutions for developers, set the cost, and maintain operational complexities.

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Selecting the right SaaS stack for your application development is not so easy. However, choosing the right tools, and technologies parallel to your project’s objectives is imperative. Also, you need to evaluate the pros and cons of your chosen tech stack so that it may not end in a financial disaster.

Have a quick walkthrough of widely used tech stacks and how to choose the right one for your business: SaaS Tech Stack

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The goal of DevOps is to boost a team’s or organization’s capacity to deploy applications more quickly. It entails building a culture around a set of best practices that focus on enhancing products in comparison to conventional development methods.

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When it comes to monitoring and observability, these two concepts are often confused with one another. However, they are different in many ways.

Monitoring is a process that involves collecting data from the application and storing it in a central repository. In other words, it’s an automated process which collects information about an application over time and stores it in a database. For example, if you have an application that runs on a server, then you can use monitoring tools like New Relic to collect this data.

Observability can be thought of as the ability of an application to generate logs or metrics that are useful for debugging or monitoring purposes. The key difference between observability and monitoring is that observability requires developers to instrument their code in order for it to work properly whereas monitoring does not require any changes at all (other than installing a tool).