Organizations begin preparing for compliance soon as they deploy their infrastructure on the cloud. While cloud compliance covers myriad regulatory requirements, such as the General Data Protection Regulation (GDPR) and Personal Data Protection Act (PDPA), it ensures cybersecurity underlined by best practices to be followed by organizations.
Compliance, similar to a robust cybersecurity framework, is a key enabler of business and its absence instills heavy monetary impacts in the case of both on-premise and cloud deployment. What is the cost of compliance? Are organizations saving costs by remaining non-compliant? Understanding this is imperative in the world of modern business where cyberattacks continue to grow sophisticated.
Non-Compliance Cost And Its Repercussions
Several organizations had rationalized the non-compliance cost to be lesser than it is needed for bringing data and technology processes under compliance. However, the impact of non-compliance cost is jaw-dropping compared to the cost of compliance with regulations such as PCI-DSS, HIPAA, GDPR, and so on.
Recent years have seen high recommendations for compliance regulations to prevent legal implications, consequences regarding business reputation, and possible fines. A prime example of penalty would be the case where RBI charged 4.5 Cr INR to IndusInd Bank for non-compliance with certain regulations. As regulations evolve and emerge, organizations look to move critical systems, infrastructure and applications to the cloud.
It has been witnessed that the demand for audit evidence requests is increasing and organizations, one in six times, are found non-compliant. This has resulted in huge fines when screened by third-party auditors. The majority of organizations believe that compliance becomes a problem while moving systems, infrastructure, and applications to the cloud. They think that challenges come to the fore while dealing with IT security compliance in the cloud.
Remain Compliant to Save Cost
With compliance violation costs growing exponentially, phasing into compliance becomes a smart move for organizations. Key components that add up to compliance costs include
Data Protection: Enforcing data usage norms and preventing data loss or leakage.
Certification: Ensuring that the business remains certified and up-to-date against all necessary compliance regulations.
Assessments: Inspection and examination of the current state of infrastructure for implementing the compliance framework as needed.
Security Investments: This involves, data encryption, data loss prevention, and governance. Investments into technology solutions enable facilitated transformation of organizations, strengthening their compliance posture.
Policies: Developing policies within an organization helps develop the structure required for complying with different regulation frameworks.
Leading cloud security and compliance solution providers, such as Cloudlytics, help organizations manage everything from risk identification to mitigation. Whether organizations need to outsource the management of their infrastructure or simply seek system optimization, vendors offer personalized solutions that enable cost savings while ensuring the infrastructure to be an asset and not a liability.
To Sum Up
Compliance costs are significantly lower than that of non-compliance and leveraging technology solutions helps reinforce the process further. Holistic approaches are necessary for ensuring data compliance, security, and protection. As key functionalities of businesses evolve, surrounding malware protection, data usage, and backup, and audit applications, a number of AI-driven compliance solutions are coming to the fore. These solutions help shore up compliance programs, thereby avoiding risks and preventing costly repercussions of non-compliance.
Load balancers are a regular phenomenon in cloud systems. You get to know about two load-balancing choices if you are using AWS: ELB and ALB. While having options is usually beneficial, the ELB Vs ALB Vs NLB argument can be worrisome. Often the question arises that what is the best load balancer for your app?
All load balancers are tailored to a specific circumstance. AWS offers three types of load balancers: elastic load balancer, application load balancer, and network load balancer. This article addresses all these concerns and offers you a proper understanding of the load balancers. Let’s now understand the concept of load balancing in the following article.
What is Load Balancing? – An Introduction
Load balancing is the process of evenly spreading incoming data traffic among a collection of backend computers. Moreover, it is popular as a server pool or server farm.
Standard high websites must handle a large number of concurrent user or client requests while returning accurate text, photos, multimedia, or application programs consistently and accurately. The best practice of digital computing often necessitates the addition of extra servers to an affordable scale to handle such high loads.
A load balancer resides next to your servers and act as a “traffic officer.” It directs customer requests across all web servers that are capable of satisfying those requests in a way that maximizes efficiency. Also, it offers greater resilience while ensuring that no single server overworks and potentially degrades its effectiveness.
When a single server goes down, the load balancer redirects requests to the existing web servers. The load balancer starts routing responses to a different server once it is assigned to a server group. Depending on the functions, load balancing is of three types: ELB, ALB, and NLB. Therefore, this article will offer a proper knowledge of all the types and ALB vs ELB performance.
Features of Load Balancing
A load-balancing accomplishes the following features:
First, disperses user requests or network capacity adequately among numerous servers.
Sends queries to only online servers, ensuring excellent stability and performance.
Allows you to add or remove servers as necessary, depending on demand.
What is Classic Load Balancing? and why is it redundant now?
Classic Load Balancer runs at both the request and connection levels and includes adequate load balancing across many Amazon EC2 instances. The purpose of Classic Load Balancer is designed for applications that use the EC2-Classic network. It decides where to route traffic at the transport layer (TCP/SSL) or the application layer (HTTP/HTTPS).
This load balancing needs a constant connection between the load balancer ports and the container’s instance port. Thus, classic load balancing is more similar to Traditional Load Balancer, except the digital devices that substitute real hardware to properly divide user requests and offer a clean, quick customer experience.
Clients can contact Classic Load Balancer through a single interface. This improves the application’s accessibility. In addition, with changing requirements, you can deploy and eliminate instances from your load balancer without interrupting the general flow of queries to your service.
Reason Why its Current Status is Redundant
Amazon Web Services (AWS) doesn’t recommend that you replace one of its services too regularly. Since its inception in 2009, CLB has been the backbone of AWS’ massively scalable systems, dependably servicing and spreading our traffic.
These classic load balancers have mostly been phased out instead of AWS’s next-generation (v2) load balancers, and you now have a couple of choices. An Application Load Balancer works at Layer 7 (application), and a Network Load Balancer that works at Layer 4. (transport).
The load balancer you choose is determined according to the layer of the underlying network your workload requires it to function at.
What is Elastic Load Balancing?
Elastic Load Balancing (ELB) is a load-balancing solution that distributes incoming network applications autonomously and adjusts resources to suit requirements.
An IT team can use an ELB server to change capacity depending on the incoming application and network load. Clients activate ELB inside a particular availability zone or even across many availability zones to ensure constant performance metrics.
Objectives of the Elastic Load Balancing
The Classic ELB incorporates a range of capabilities that can assist your application stack in achieving high reliability, management, and protection. ELB has several objectives, including the following:
Identification of Elastic Compute Cloud (EC2) servers that are hazardous.
Only distribution of instances among trustworthy channels.
Endorse for a variety of ciphers.
Centralized administration of Secure Sockets Layer (SSL) certificates.
Essential verification with a public key.
Enabling support for both IPv4 and IPv6.
What is an Application Load Balancer?
The AWS Application Load Balancer (ALB) is part of the OSI model’s Layer 7 layer. The ELB can examine application-level material at Layer 7, not simply port numbers and IP. This enables it to route traffic according to more strict systems than the Classic Load Balancer. Overall, the ALB is more complex considering the comparison of application load balancer vs elastic load balancer.
An Application Load Balancer routes connections to one or even more ports across each container instance in a network, determining routing decisions at the application layer and providing path-based routing. This happens with the use of Service Load Balancing that interacts with the ECS (EC2 Container Service).
Mostly, the ALB assists the dynamic host port mapping. Within this EC2 instance, many containers can be addressed, each executing multiple programs on various ports. Following this, the ECS task scheduler automatically transfers this to the ALB.
Characteristics of an Application Load Balancing
Following are the essential characteristics and features of Application Load Balancing:
Assists to the HTTP and HTTPS protocols
Adding an ideal group to an Auto Scaling group, dynamically scales each service that depends on the requirements.
Its sticky Sessions feature allows you to redirect requests from the same client to the same objective using cookies.
Achieve optimal availability by enabling the selection of several AZs and spreading incoming traffic across numerous AZs.
Incorporates with ACM to issue and assign an SSL/TLS certificate, simplifying the SSL offload procedure.
What is Network Load Balancer?
A Network Load Balancer manages both TCP and UDP interactions and TCP links encrypted using TLS. The NLB only operates at layer 4. Its key feature is that it performs exceptionally well. Also, it employs static IP addresses and can allocate the Elastic IPs, which ALB and ELB cannot do.
NLB is capable of processing millions of queries per second. When the load balancer obtains a request, it uses a flow hash routing mechanism to choose a goal from the target group for the condition precedent. Then, it seeks to link to the target node through TCP on the port given in the listener settings.
Without any alteration in the headers, it directs the requests. Moreover, the NLB offers support for dynamic host port mapping. Anything that ALBs miss to cover. NLB successfully performs that task. A real-time information streaming platform is an example of a typical use application. Also, you will require the use of NLB when your app employs non-HTTP interfaces.
Benefits of Employing NLB
Employing an NLB can offer several advantages to its users. Following are the significant benefits of NLB to focus on:
First, diagnose and restore a cluster host that has crashed or gone offline.
As hosts are introduced or withdrawn, it adjusts the network load accordingly.
Utilizing port management guidelines, you can define the load-balancing behavior for a specific Ip port or a collection of ports.
Whenever the impact on the cluster lessens, it removes hosts from the cluster.
Bans the unwanted network connection to specific IP ports.
Comparison Table of Each of the Load Balancers
When talking about all the load balancers, it becomes essential to make a comparison among ELB vs ALB vs NLB. So let’s first take a gander regarding the common points among all three types of load balancers. Since all these load balancers are AWS products, they will share some of the similarities.
The first similarity is the incoming requests that are distributed to various targets. These targets are either EC2 instances or Docker containers. Following, they all have health checks and balances in place to detect unsafe situations. Next, they are all easily accessible and adaptable.
Finally, all three ELBs, ALBs, and NLBs may export helpful metrics to CloudWatch and report relevant data to CloudWatch Logs. The following table supports the users to get to know the best appropriate load balancer for their use. So, here is all you need to check while comparing all the three load balancers that help in selecting the suitable one.
Application Load Balancer (ALB)
Network Load Balancer (NLB)
Elastic Load Balancer (ELB)
Layer 4 (TCP)
Layer 7 (HTTP)
Perform Health Checks
Preserve Source IP
Advance Routing Choice
Assists User Authentication
Usable in EC2-Classic
Assists Docker Containers
Assist Targets External to AWS
Talking about load balancing, AWS provides a plethora of choices, and you can probably find what you need online. Almost everyone uses the AWS load balancers, and it also has endured the test of time. They are quite dependable.
All the three load balancers share an easily comparable price. This is uncertain to have a major impact on your selection. Hopefully, this article about ELB vs ALB vs NLB will assist you in gaining a better grasp of load balancers.
Observability is a prominent topic, with many discussions focusing on the distinction between observability Versus monitoring. Both systems are essential for system reliability, but eventually, they are different. Monitoring is a critical component in high-performing organizations.
A complete observability and monitoring solutions, including a variety of other technological approaches, favourably add to order fulfilment. However, precisely, the question is, “what is observability,” and “how is it different from monitoring?”
Let’s look at how controllability and observability vary and whether they are both important for flexibility and control in cloud-based corporate IT processes.
What is Observability?
Observability is the activity of extracting meaningful insights from data provided by engineered IT and technological systems. It is predicated on discovering properties and patterns that aren’t known ahead of time. The aim is to figure out why and when an incident or problem transpired.
We can examine how well a system functions without meddling or even engaging with it if it is a visual system. Observability combines three kinds of sensor information — traces, metrics, and logs. These data then offer comprehensive visibility into distributed databases. Also, it helps organizations pinpoint the source of a variety of problems and enhance the performance of a system.
Observability enables organizations to monitor current systems more effectively, locate and correlate effects in a complicated chain, and track them back to the source. Thus, we can say that there is an interlink connection between controllability and observability. It also provides IT operations analysts, network administrators, and developers with a comprehensive view of their systems.
Goals and Objectives
The goal of observability is to receive information from the outputs and react accordingly. Consider the following example:
Determine the percentage of defects in all functions.
Observe traces that indicate a delay between specific function operations and transitions between elements to discover inefficiencies in microservices.
Determine when and for how long your code executes.
Identify trends of when problems or obstacles occur and utilize the information to take measures to prevent future occurrences.
What is Monitoring?
Monitoring is an act that has an association with observability. Observing the efficiency of system stability and performance across the times. The monitoring activity, which instruments and procedures assist, can characterize a system’s internal states’ effectiveness, health, and pertinent attributes.
Monitoring is the process of converting network log metrics data into valuable and actionable insights in organizational IT. The network log metrics’ capacity to deduce the technical specifications related to various elements is part of a system’s observability property. Monitoring software examines infrastructure log information to provide actions and insights.
Goals and Objectives
The eventual aim of monitoring is to keep track of a program’s health through a constant gathering of error reports and system data. This translates to:
Tracks and warns the errors as promptly as possible.
Uses alerting, alarms, and warnings to respond to failures and security attacks.
Analyzing data such as CPU utilization or network traffic to determine whether or not specific computing capabilities are functional
Monitoring Vs Observability – Key Differences
Observability and monitoring share an inextricable link. Monitoring will provide you with data and information regarding your network and notify you if there is indeed a failure. However, observability can provide you with a simple opportunity to analyze exactly the path and reason for the loss.
You acquire observability when desirable information from the inside network that you want to monitor is publicly disclosed. The task of gathering and showing this data is known as monitoring. When discussing “observability vs monitoring,” there is one more important concept to remember, that is, “analysis.”
However, here are some of the critical differences between observability and monitoring to follow:
Consumes data Complacently
Seek knowledge actively
Create a set of questions depending on the dashboards.
Pose to inquire that depends on hypothesis.
Designed to keep environments as consistent as possible.
Designed to control changing intricacy in dynamic contexts
Developers of systems with low variation and known permutations use this method.
Developers of systems with a lot of unpredictability and unknown permutations prefer it.
Nature is responsive.
Nature is proactive.
Allows for prompt response in the event of an issue.
Decreases the length and severity of incidents.
Observability in DevOps
In DevOps, the capacity to obtain valuable intelligence from monitoring tool logs is referred to as observability. You can better understand the development and well-being of your systems, apps, and infrastructures using these insights.
The following are the significant components of observability in DevOps:
Logging: It is used to maintain track of occurrences to make the team learn from prior events and locate the source and cause of a problem faster.
Tracing: It allows for the knowledge of the connection between a problem’s source and consequence. In the end, it improves the effectiveness of the visual system and facilitates root cause analysis.
Metrics: These are the numerical information provided, and they allow engineers to discover trends.
One of the essential advantages of observability is the ability to translate large amounts of data into practical and understandable insights. Using observability gives you access to information about how to tackle problems.
How does Cloudlytics act as a tool for observability?
You will need to have a specialized collection of tools to visualize the operations that warn you of failures occurring. Then, you can use the tool to analyze system behaviour better and avoid future issues. For “Observability vs Monitoring,” we go over the most popular observability system that is Cloudlytics.
Cloudlytics delivers real-time insight into cloud infrastructure and applications on Azure, AWS, and GCP. With the help of this tool, you can scale, monitor, and optimize in any cloud.
Frequently Asked Question (FAQ)
What do you know about the tools used for observability?
An observability tool is a program that uses monitors and logs to keep track of tools and networks. Observability tools, with the exception of specific monitoring tools, allow a company to have continual insight and input from its networks.
What is observability in terms of KPIs?
DevOps observability is the technique of combining KPIs from creation to distribution, or the whole application development process, to improve speed and efficiency, system stability, and technology innovation.
What are the advantages and disadvantages of controllability and observability?
Controllability and observability are two crucial features of state models to investigate before constructing a controller. As a result, if a condition isn’t observable, the controller won’t be capable of predicting its behaviour from the control system. As a result, neither can utilize it to stabilize the system.
As the majority of businesses extensively embrace digital services, threat factors are becoming sophisticated in stealing data by compromising systems. From filtering traffic to validating access, cloud security solutions safeguards organizations from all these cyber threat factors by building an array of authentication rules. The traditional security measure, network security, on the other hand, ensures data security through computing parameters.
Among numerous trends and innovations governing business development across the globe, cyber security is seen as a top priority. Also, organizations are constantly prowling to ensure they maintain pace with cyber security developments. However, while doing so, it is imperative for organizations that they fundamentally understand the difference between the cyber security types, among which network and cloud security remain predominant.
Cloud Security Vs Network Security – Key Differences
While cloud security offers wider protection, including information, data, applications, and computing environment, network security solutions involves a bunch of practices and policies that monitor and prevent unauthorized data access or modification. Created by using numerous segments of equipment and programming, network security converges just on protecting networks.
Both network security and cloud security have few overlapping nodes of events. They both demand highly advanced features, constant monitoring, and increasing storage space for maintaining a resilient security environment. However, when seen as different entities, there is a potential harnessing various benefits regarding cloud based security.
The pinnacle of the software and hardware blend, network security solutions ensures protecting databases. Also, the data under network security is difficult to access by the cloud security environment.
Various challenges are associated with network security, as it involves use of both software and hardware, which results in the high cost of maintenance. Cloud computing security, completely nesting in software, significantly ebbs the cost parameter.
Cloud security is highly permeable, allowing flexibility in the development of security systems. Using best practices and techniques, organizations are allowed to make their cloud security as complicated as they desire for ensuring data protection. This is highly challenging in the case of network security.
Network security solutions relies on authorization systems that demand network administrator access on every instance of data access by users. This helps organizations secure networks while overseeing and protecting operations. Cloud security, on the other hand, prevents unauthorized data access, DDoS attacks, malware, and hackers that target systems.
While cloud security works on identity and access management, web application firewalls, and encryption, network security brings together multiple check barriers at all layers using controls and policies of protection.
Cloud security radically transforms network security enabling security against attacks and maintaining regulatory compliance while providing agility, updates, and physical protection. However, it is vital for organizations to understand that cloud security is a shared responsibility that involves participation of both cloud service providers (CSPs) and themselves.
To Sum Up
Cloud security, without doubt, is the preferable choice for organizations to keep their data safe. Unlike network security, cloud security delivers greater cost, control, and safety benefits. To utilize enhanced security options, organizations must focus on partnering with the right service providers that provide seamless transition with advanced features.
The global cloud infrastructure is nothing but addressing data requests of organizations from across the world. The opaque nature of the cloud industry has been a disadvantage for organizations and they have been continuously searching for transparency for assessing vendor claims and mitigating financial risks. The cloud service providers (CSPs) have been making efforts to offer organizations the right information and help them make informed decisions driven by data.
Trust has been the foundation of relationships between leading cloud technology providers and organizations. Being transparent about products and services is the reinforcement of that foundation. The cloud service providers are therefore committed to transparent sharing of information to solidify their relationships with organizations. Organizations look for transparency into the supply chain for assessing the sales claims of CSPs and mitigating financial risks.
The Need for Transparency
There have been concerns among organizations regarding clarity with their CSPs. A key reason behind this is that the CSPs do not unveil anything about their claims of the state-of-the-art security measures. Organizations will be better able to believe in their cloud service provider if they clearly represent that they are in compliance with their corporate requirements. Being transparent in their practices is of utmost importance for CSPs.
There are multiple ways where the cloud service providers can gain loyalty of organizations. These measures range from verifying the background information to conducting onsite audits . However, realizing a completely transparent system is challenging, particularly for SMEs, unlike large organizations who can demand transparency from their cloud service providers.
It has been seen that organizations are still reluctant to completely deploy their infrastructure on the cloud, as they look for CSPs to fulfil compliance requirements of the corporate world. Also, the growing number of data breaches in recent years has driven organizations to be cautious about putting trust in their cloud vendors regarding their sensitive data.
There is an urging need for clarity in every contract on issues that influence and raise concerns among organizations worldwide. The onus remains on CSPs who are expected to take measures for providing greater transparency about poor performance and service disruptions. These measures must further be backed up legally for gaining trust among potential consumers of cloud services. The real challenge is in wordsmithing the legalese. From the perspective of technology, to deliver SLA transparency clauses, application performance technologies are required to enhance visibility in operations and systems.
How Can Transparency Be Achieved
The cloud service data, when collected through automation with the help of software APIs, enables effective comparisons of the services. However, this approach is still at its nascent stage. As cloud computing continues to evolve and gain high popularity in the market for enterprise IT deployments, new industry analysis techniques are emerging for understanding the supply chain of cloud services.
Listing the cloud services with software automation will prevent exposure of capabilities that are internal to organizations and their operations. This can be a good start for organizations and cloud services providers to achieve transparency.
As organizations across the world continue their digitization efforts, it has become clear to them that security must be ceaseless rather than security-as-a-stage implemented at the end of operations and development lifecycles. The security technology, particularly the security principles and functions, are advancing in parallel. Organizations are aware that securing their data and then safeguarding it is an important responsibility.
Navigating the spectrum of cloud security in an ever-changing landscape of regulations while following the security principles is a challenging task. The more complex the infrastructure of an organization is, the more difficult it is to maintain compliance as regulations evolve. It is imperative that organizations balance their need for securing data with the cloud’s flexibility.
Cloud Security Principles that Organizations Must Focus On
Being transparent about security practices helps organizations strategize a successful approach to cloud security. Following are some important security principles that must be considered while designing and implementing the cloud security roadmap.
The networks that transition the user data must have a robust protection against eavesdropping and tampering. A combination of encryption and network protection helps organizations achieve this. It helps them arrest the attacker’s ability to compromise data and read data.
Protecting the Data at Rest
Ensuring unavailability of the data to unauthorized users with access to the infrastructure is a must. The user data must be protected irrespective of its storage media. Inadvertent disclosure or loss of data could be the risk if proper measures aren’t put in place.
The assets that store or process the user data need protection against any seizure, damage, or tampering. Key aspects to consider include equipment disposal, data center security, protecting the data at rest and in transit, availability, resilience, and data sanitization.
Securing the Data Center
Cloud services require physical protection against reconfigurations, tampering, unauthorized access, and attacks. Physical security is completely offered by leading cloud providers, which encompasses a broad range of attestations and certifications. Improper protection measures eventually result in data alliteration, loss, or disclosure.
Sanitizing the Data
The process of migrating and provisioning resources must not lead to any unauthorized access to the user data. Improper data sanitization results in data retention, inaccessibility, or data loss.
Equipment used for delivering services, once they are at the end of their lifecycle, must be trashed in a way that doesn’t compromise the user data and the security framework. Therefore, CSPs make it a point that the equipment disposal is ensured as a top responsibility.
Resilience and Availability
The level of resilience in security varies, which impacts their operations in the case of an attack, incident, or failure. Lack of availability can undermine the whole security strategy, which potentially prolongs regardless of business impacts.
The security strategy must not allow any compromised or malicious user to affect the sensitive data of another. There are some factors that affect user separation. These include the location of separation controls implemented, data sharing, and the degree of assurance in implementing separation controls.
Securing the Operations
The operations and their management must be highly secure to identify, mitigate, or prevent attacks. A good operational security doesn’t mean that a complex, time-intensive process must be followed. Key elements to consider here are change management, configuration, proactive monitoring, incident management, and vulnerability management.
The security governance framework must coordinate and direct the management of the framework within it. It must do so in order to undermine any deployment of technical controls from outside the framework. An effective governance framework ensures continued technical and physical controls throughout the lifetime of the security roadmap.
To Sum Up
There are many challenges and areas for advancement in cloud security, and security principles can help the organizations fill these gaps. All users and organizations themselves must be well aware of threats that lurk in the cloud security landscape. Organizations must plan well for balancing their cloud security budget and activities with user convenience and time-to-market.